This study aims to examine the global scientific landscape of technology transfer in the renewable energy sector through bibliometric analysis. It addresses the key question of how research on renewable energy technology transfer has evolved worldwide and which studies, authors or institutions have shaped its progression. The study also analyzes how these dynamics influence innovation, policymaking and sustainable development in emerging economies.
A bibliometric analysis was conducted using 362 peer-reviewed journal articles retrieved from the Scopus database, covering the period from 1981 to July 2025. VOSviewer and Harzing’s Publish or Perish software were used to analyze co-authorship networks, keyword co-occurrence, citation structures and geographic research distribution.
This study elucidates the evolution of global research on renewable energy technology transfer and its implications for innovation, policy and sustainable development in emerging economies. Findings show a surge in output since 2018, led by China, the United States and the UK, with themes shifting from conceptual debates to applied issues such as energy security, foreign direct investment and institutional capacity, while offering practical insights for effective technology transfer strategies.
Theoretically, it is among the first systematic bibliometric analyses of renewable energy technology transfer, mapping its intellectual structure and collaboration patterns over four decades. In practice, it provides evidence-based insights for researchers and policymakers to enhance innovation, foster cross-border cooperation and design effective technology transfer strategies.
1. Introduction
In the face of globalization and climate change, a shift to renewable energy is vital for sustainable development (Yi et al., 2023). This transition depends on technological innovation and mechanisms for cross-border transfer, allowing developing economies to adopt low-carbon solutions, as shown by China’s solar initiatives, while expanding access to clean, affordable power (Jackson et al., 2021) and supporting SDG 7.
To support this transition, research on renewable energy technology transfer has expanded to include cross-border mechanisms (Khezri and Hasan, 2024), foreign direct investment (FDI) (Gillani and Abbas, 2025; Nassani et al., 2025), absorptive capacity (Edze, 2025; Hötte, 2020), and the roles of policy frameworks and institutional actors. These studies underscore its importance for business strategy, energy policy, and innovation systems. Despite this progress, the field remains fragmented, with limited integration of long-term trends, key contributors, and emerging themes.
This study makes a twofold contribution. Academically, it provides one of the first systematic bibliometric analyses of renewable energy technology transfer, mapping its intellectual foundations, thematic evolution, and collaboration patterns over 4 decades. From a policy perspective, it delivers evidence-based insights to help governments and international organizations embed technology transfer into climate and energy transition strategies.
This perspective can assist emerging economies in strengthening innovation capacity and institutional frameworks. Through the bibliometric analysis of Scopus publications, this study addresses the following questions:
How has research on renewable energy technology transfer evolved over time?
Which are the most influential authors, countries, and journals shaping this field?
What patterns of international research collaboration characterize this domain?
Answering these questions provides a structured overview of the field, offering actionable insights for policymakers, industry leaders, and researchers. This overview highlights how technology transfer can be embedded in climate-aligned energy transition plans. It guides businesses in identifying opportunities for collaboration and provides academics with a framework to study cross-border knowledge flows. Simultaneously, it underscores the importance of international cooperation and institutional capacity-building in promoting renewable energy.
2. Literature review
2.1 Types of technology transfer
Technology transfer refers to the movement of knowledge, expertise, technologies, and processes across organizations or countries to improve products, services, or production systems. It is widely recognized as a driver of economic growth, technological upgrading, and sustainable development (Bozeman, 2000; Marín-García et al., 2025).
Three main forms of technology transfer have been identified. Horizontal transfer occurs between entities with similar technological capabilities, such as between wind turbine firms in different countries. Vertical transfer involves the transition from research and development to commercialization (Howells, 1996). Finally, international transfer describes flows from developed to developing countries, thereby reducing technological gaps and fostering capacity in emerging economies (Bozeman, 2000). These types suggest that this process is multidimensional, with each pathway having different implications for renewable energy adoption.
2.2 Institutional and policy barriers
In renewable energy, technology transfer is essential for progressing to a low-carbon economy (Lee et al., 2017). The deployment of solar, wind, and biomass energy sources requires substantial capital and expertise, which are often limited in developing contexts (Leal Filho et al., 2025). Effective transfer can build technological capacity (Fernández, 2025; Wang et al., 2025), accelerate access to clean solutions (Wu and Xu, 2025), and promote energy efficiency and green growth (Pueyo, 2013). It also enables knowledge sharing, process improvement, and the growth of clean technologies (Gu et al., 2021).
Despite these benefits, outcomes are shaped by institutional and policy conditions. Absorptive capacity, regulatory support, and FDI and clean development mechanisms strongly influence success (Gillani and Abbas, 2025; Nassani et al., 2025), whereas weak governance, insufficient training, and inadequate infrastructure remain significant barriers. Although the literature emphasizes the importance of enabling institutions, systematic assessments of these mechanisms remain limited.
2.3 Role of emerging economies
In emerging economies, technology transfer is a critical driver of innovation, energy security, and industrial upgrading. These countries face the dual challenge of meeting rising energy demand while transitioning to lower carbon emissions. China, now the world’s largest solar PV manufacturer, exemplifies this shift by exporting panels, services, and production capacity, thereby establishing new South–South transfer channels (Jackson et al., 2021). Moreover, the industrial collaboration has accelerated low-carbon transitions by generating knowledge spillovers and resource synergies across firms and institutions (Wu and Xu, 2025). India has likewise emerged as a major contributor to digital–energy integration and clean energy research (Apeh and Nwulu, 2025). Such cases highlight how emerging economies increasingly act not only as recipients but also as sources of renewable energy knowledge, strengthening domestic industries, fostering employment, and enhancing resilience to external shocks.
However, the effectiveness of technology transfer varies across countries, reflecting disparities in capacity and institutional quality (Wang et al., 2025). Countries such as Brazil, South Africa, and Indonesia demonstrate both the promise and the limits of South–South cooperation: while these partnerships facilitate adaptation and diffusion of renewable technologies, persistent gaps in governance, financing, and infrastructure constrain their impact (Leal Filho et al., 2025). Systematic analysis of these dynamics is therefore essential to unlock the potential of South–South collaboration for sustainable energy transitions.
2.4 Research gaps
Although research on renewable energy technology transfer has expanded, several important gaps remain. Limited attention has been given to domestic diffusion, particularly how countries adapt, scale, and embed transferred technologies. Comparative assessments across solar, wind, and biomass sectors are also scarce, leaving differences in transfer pathways underexplored. Moreover, there is insufficient analysis of how institutional frameworks and policy mechanisms condition technology transfer outcomes in emerging economies. To address these shortcomings, this study applies a bibliometric approach to map academic output, collaboration networks, and thematic shifts, linking technology transfer research more closely with policy and innovation in emerging economies. It extends earlier reviews by covering more than 4 decades, focusing exclusively on renewable energy technology transfer, and integrating both conceptual and regional perspectives.
3. Methodology
Bibliometric analysis is a quantitative approach used to organize and assess scientific publication data. It assists researchers in understanding the development of a research field by identifying emerging themes, evaluating scholarly impact, and highlighting gaps for future research (Sharma et al., 2022; Yang and Wang, 2025). This technique enables systematic analysis of large datasets by examining relationships among publications, authors, citations, and keywords through network visualizations (Donthu et al., 2021). It has proven valuable for both early-career and experienced researchers in selecting suitable journals, mapping academic networks, assessing research impact, and guiding strategic collaboration and funding (Alfawareh et al., 2025). Accordingly, this study uses bibliometric analysis to investigate technology transfer within the renewable energy sector as a dynamic and developing research domain.
The dataset for this analysis was obtained from the Scopus database, which is widely recognized in bibliometric research for its comprehensive coverage, detailed metadata, and accessibility (Block et al., 2020; Pranckutė, 2021). Compared with the Web of Science (WoS), Scopus offers broader disciplinary and regional coverage, particularly in energy and environmental studies (Pranckutė, 2021; Rodrigues et al., 2025). Databases such as Dimensions and OpenAlex, while valuable, were not retained because their indexing standards and citation structures are less consistent for longitudinal analyses, potentially affecting data comparability. Nevertheless, the exclusive reliance on Scopus may result in minor selection bias, especially regarding non-English or region-specific publications. Following established bibliometric procedures (Islam et al., 2025; Mohd Aripin et al., 2025; Sharma and Sengar, 2025), a keyword-based search strategy was applied to titles, abstracts, and author keywords to ensure thematic precision while maintaining broad coverage of renewable energy technology transfer studies. The inclusion criteria were restricted to peer-reviewed journal articles published in English in their final form and classified as journal-type sources.
Data were retrieved from Scopus using the following search query: (TITLE-ABS-KEY (renewable energy) AND TITLE-ABS-KEY (technology transfer)) AND (LIMIT-TO (DOCTYPE, “ar”)) AND (LIMIT-TO (PUBSTAGE, “final”)) AND (LIMIT-TO (LANGUAGE, “English”)) AND (LIMIT-TO (SRCTYPE, “j”). The articles were collected throughout all years to provide a comprehensive overview of the topic’s evolution. The data collection and processing procedure, which followed the PRISMA model, is illustrated in Figure 1.
The flowchart starts from the top, the first text box labeled “Topic” connects by a rightward arrow to the second text box labeled “Technology Transfer in Renewable Energy”, and connects through a downward arrow to the third text box labeled “Keywords and Search”, which connects through a rightward arrow to the fourth text box labeled “Renewable energy” AND “Technology transfer”. A downward arrow connects the third text box to the fifth text box labeled “Scope and Coverage”, which is further connected through a rightward arrow the sixth text box labeled “Database: Scopus database”, “Field: Article title, keywords, and abstracts”, “Publication stage: Final”, “Language: English”, “Document type: Article”, and “Source type: Journal”. A downward arrow from the fifth text box leads to the seventh text box labeled “Records Identified and Screened”, which is further connected through a rightward arrow to the eighth text box labeled “N equals 2348”. A downward arrow from the seventh text box leads to the ninth text box labeled “Records Removed”, which is further connected through a rightward arrow to the tenth text box labeled “N equals 1986”. A final downward arrow from the ninth text box leads to the eleventh text box labeled “Records Included for Bibliometric Analysis”, which is further connected through a rightward arrow to the twelfth text box labeled “N equals 362”.Scopus-based data collection process. Source(s): Created by authors
The flowchart starts from the top, the first text box labeled “Topic” connects by a rightward arrow to the second text box labeled “Technology Transfer in Renewable Energy”, and connects through a downward arrow to the third text box labeled “Keywords and Search”, which connects through a rightward arrow to the fourth text box labeled “Renewable energy” AND “Technology transfer”. A downward arrow connects the third text box to the fifth text box labeled “Scope and Coverage”, which is further connected through a rightward arrow the sixth text box labeled “Database: Scopus database”, “Field: Article title, keywords, and abstracts”, “Publication stage: Final”, “Language: English”, “Document type: Article”, and “Source type: Journal”. A downward arrow from the fifth text box leads to the seventh text box labeled “Records Identified and Screened”, which is further connected through a rightward arrow to the eighth text box labeled “N equals 2348”. A downward arrow from the seventh text box leads to the ninth text box labeled “Records Removed”, which is further connected through a rightward arrow to the tenth text box labeled “N equals 1986”. A final downward arrow from the ninth text box leads to the eleventh text box labeled “Records Included for Bibliometric Analysis”, which is further connected through a rightward arrow to the twelfth text box labeled “N equals 362”.Scopus-based data collection process. Source(s): Created by authors
VOSviewer software was used to visually map the relationships among keywords, authors, organizations, and countries, thereby enabling a systematic and intuitive analysis of the scientific network using advanced layout algorithms (Alfawareh et al., 2025). Harzing’s Publish or Perish software was employed to collect citation metrics and identify the most influential publications in the field (Alfawareh et al., 2025; Mehmood et al., 2024). The results were synthesized from both conceptual and regional perspectives, providing a comprehensive analysis to draw conclusions, identify limitations, and propose future research directions.
Figure 1 summarizes the systematic data collection and screening procedure applied in this study, following the PRISMA framework. This process ensured transparency, reproducibility, and the reliability of the dataset used in subsequent analyses.
4. Results
4.1 Publications per year
The field attracted little attention for nearly 2 decades after the first article in 1981 (Mackillop, 1981), reflecting the limited policy and academic interest in renewable technologies at the time. The number of publications steadily increased after 2009, coinciding with the global financial crisis, the adoption of international climate agreements, and rising investment in clean energy. Output peaked in 2024 with 35 articles and remained high during the first five months of 2025.
Figure 2 shows the number of publications on renewable energy technology transfer from 1981 to 2025. These trends suggest that research on technology transfer has mirrored global shifts in energy policy, climate governance, and innovation, indicating its emergence as a central theme in sustainability studies.
The line graph titled “Number of Publications per Year”. The vertical axis is labeled “Number of Publications” and ranges from 0 to 35 in increments of 5 units. The horizontal axis has markings “1981”, “1985”, and from 1990 to 2025, in increments of 1 year. The plotted line shows a fluctuating trend. The line starts at (1981, 1), (1985, 2), (1990, 4), (1991, 1), (1992, 2), (1993, 5), sharply peaks to (1994, 14), then declines to pass through (1995, 2), (1996, 6), (1997, 3), (1998, 3), (1999, 3), (2000, 4), (2001, 6), (2002, 1), (2003, 1), (2004, 3), (2005, 9), (2006, 9), (2007, 7), (2008, 4), (2009, 11), (2010, 12), (2011, 11), (2012, 10), (2013, 12), (2014, 11), (2015, 19), (2016, 11), (2017, 9), (2018, 20), (2019, 12), (2020, 19), (2021, 17), (2022, 18), (2023, 23), peaks to (2024, 35), and terminates at (2025, 22).Number of articles published annually. Source(s): Created by authors
The line graph titled “Number of Publications per Year”. The vertical axis is labeled “Number of Publications” and ranges from 0 to 35 in increments of 5 units. The horizontal axis has markings “1981”, “1985”, and from 1990 to 2025, in increments of 1 year. The plotted line shows a fluctuating trend. The line starts at (1981, 1), (1985, 2), (1990, 4), (1991, 1), (1992, 2), (1993, 5), sharply peaks to (1994, 14), then declines to pass through (1995, 2), (1996, 6), (1997, 3), (1998, 3), (1999, 3), (2000, 4), (2001, 6), (2002, 1), (2003, 1), (2004, 3), (2005, 9), (2006, 9), (2007, 7), (2008, 4), (2009, 11), (2010, 12), (2011, 11), (2012, 10), (2013, 12), (2014, 11), (2015, 19), (2016, 11), (2017, 9), (2018, 20), (2019, 12), (2020, 19), (2021, 17), (2022, 18), (2023, 23), peaks to (2024, 35), and terminates at (2025, 22).Number of articles published annually. Source(s): Created by authors
4.2 Research areas of publications
According to Figure 3, which shows the number of publications by subject area, work on renewable energy technology transfer is concentrated in a few core disciplines. Energy accounts for 219 publications and environmental science for 183 publications, together making up more than half of the total output. This concentration reflects the technical and environmental focus that has shaped the field since its early development. Social sciences, with 80 publications, and engineering, with 74 publications, provide important perspectives by examining institutional, behavioral, and technological aspects. Other subject areas, including economics, management, and computer science, appear less frequently but still expand the scope of analysis. Their contribution demonstrates that technology transfer is studied not only as an environmental or technical matter but also as a multifaceted process that cuts across policy, industry, and innovation contexts.
The chart titled “Publications by Subject Area”. The horizontal bar graph displays the number of publications across 21 subject areas. The horizontal axis is labeled “Number of Publications”, with values increasing from left to right, ranging from 0 to 200 in increments of 50. The vertical axis has markings, labeled from top to bottom as follows: “Energy”, “Environmental Science”, “Social Sciences”, “Engineering”, “Economics, Econometrics and Finance”, “Business, Management and Accounting”, “Mathematics”, “Computer Science”, “Earth and Planetary Sciences”, “Agricultural and Biological Sciences”, “Chemical Engineering”, “Physics and Astronomy”, “Multidisciplinary”, “Psychology”, “Decision Sciences”, “Medicine”, “Materials Science”, “Chemistry”, “Biochemistry, Genetics and Molecular Biology”, “Pharmacology, Toxicology and Pharmaceutics”, and “Arts and Humanities”. Each subject area is represented by a horizontal bar with the exact count displayed at the right end of the bar. The data shown are as follows: “Energy”: 219 publications. “Environmental Science”: 183 publications. “Social Sciences”: 80 publications. “Engineering”: 74 publications. “Economics, Econometrics and Finance”: 39 publications. “Business, Management and Accounting”: 31 publications. “Mathematics”: 28 publications. “Computer Science”: 21 publications. “Earth and Planetary Sciences”: 10 publications. “Agricultural and Biological Sciences”: 10 publications. “Chemical Engineering”: 7 publications. “Physics and Astronomy”: 6 publications. “Multidisciplinary”: 6 publications. “Psychology”: 5 publications. “Decision Sciences”: 5 publications. “Medicine”: 4 publications. “Materials Science”: 3 publications. “Chemistry”: 3 publications. “Biochemistry, Genetics and Molecular Biology”: 2 publications. “Pharmacology, Toxicology and Pharmaceutics”: 1 publication. “Arts and Humanities”: 1 publication. All bars are uniformly colored in light blue, and the layout presents the highest publication counts at the top, decreasing progressively toward the bottom.Publications by subject area. Source(s): Created by authors
The chart titled “Publications by Subject Area”. The horizontal bar graph displays the number of publications across 21 subject areas. The horizontal axis is labeled “Number of Publications”, with values increasing from left to right, ranging from 0 to 200 in increments of 50. The vertical axis has markings, labeled from top to bottom as follows: “Energy”, “Environmental Science”, “Social Sciences”, “Engineering”, “Economics, Econometrics and Finance”, “Business, Management and Accounting”, “Mathematics”, “Computer Science”, “Earth and Planetary Sciences”, “Agricultural and Biological Sciences”, “Chemical Engineering”, “Physics and Astronomy”, “Multidisciplinary”, “Psychology”, “Decision Sciences”, “Medicine”, “Materials Science”, “Chemistry”, “Biochemistry, Genetics and Molecular Biology”, “Pharmacology, Toxicology and Pharmaceutics”, and “Arts and Humanities”. Each subject area is represented by a horizontal bar with the exact count displayed at the right end of the bar. The data shown are as follows: “Energy”: 219 publications. “Environmental Science”: 183 publications. “Social Sciences”: 80 publications. “Engineering”: 74 publications. “Economics, Econometrics and Finance”: 39 publications. “Business, Management and Accounting”: 31 publications. “Mathematics”: 28 publications. “Computer Science”: 21 publications. “Earth and Planetary Sciences”: 10 publications. “Agricultural and Biological Sciences”: 10 publications. “Chemical Engineering”: 7 publications. “Physics and Astronomy”: 6 publications. “Multidisciplinary”: 6 publications. “Psychology”: 5 publications. “Decision Sciences”: 5 publications. “Medicine”: 4 publications. “Materials Science”: 3 publications. “Chemistry”: 3 publications. “Biochemistry, Genetics and Molecular Biology”: 2 publications. “Pharmacology, Toxicology and Pharmaceutics”: 1 publication. “Arts and Humanities”: 1 publication. All bars are uniformly colored in light blue, and the layout presents the highest publication counts at the top, decreasing progressively toward the bottom.Publications by subject area. Source(s): Created by authors
Figure 3 shows most renewable energy transfer studies focus on a few disciplines, highlighting the field’s technical emphasis and growing interest from social sciences and economics.
4.3 Analysis of the 10 most cited publications
Table 1 lists the 10 most cited articles on renewable energy technology transfer published between 2005 and 2021, which together have attracted 2,959 citations. Two articles stand out. Sarkodie and Strezov (2019), with 942 citations, examined how FDI, economic growth, and energy consumption affect greenhouse gas emissions in developing countries, linking technology transfer to broader debates on sustainability. Pehnt (2006), with 546 citations, proposed a dynamic life cycle assessment framework that highlighted the temporal dimension of evaluating renewable energy systems. The remaining highly cited studies address themes such as industrial policy support, solar hydrogen systems, globalization, and sustainable taxation, underscoring the variety of perspectives shaping this field.
Top 10 highly cited articles
| Title | Authors | Year | Journal | Total citations | Citations/Year | Reference |
|---|---|---|---|---|---|---|
| Effect of foreign direct investments, economic development and energy consumption on greenhouse gas emissions in developing countries | Sarkodie S.A.; Strezov V. | 2019 | Science of the Total Environment | 942 | 157 | Sarkodie and Strezov (2019) |
| Dynamic life cycle assessment (LCA) of renewable energy technologies | Pehnt M. | 2006 | Renewable Energy | 546 | 28.74 | Pehnt (2006) |
| Fostering a renewable energy technology industry: An international comparison of wind industry policy support mechanisms | Lewis J.I.; Wiser R.H. | 2007 | Energy Policy | 441 | 24.50 | Lewis and Wiser (2007) |
| Solar-hydrogen: Environmentally safe fuel for the future | Nowotny J.; Sorrell C.C.; Sheppard L.R.; Bak T. | 2005 | International Journal of Hydrogen Energy | 372 | 18.60 | Nowotny et al. (2005) |
| Limitations of carbon footprint as indicator of environmental sustainability | Laurent A.; Olsen S.I.; Hauschild M.Z. | 2012 | Environmental Science and Technology | 298 | 22.92 | Laurent et al. (2012) |
| The impact of globalization and financial development on environmental quality: Evidence from selected countries in the Organization for Economic Co-operation and Development (OECD) | Zafar M.W.; Saud S.; Hou F. | 2019 | Environmental Science and Pollution Research | 244 | 40.67 | Zafar et al. (2019) |
| The dynamic links among energy transitions, energy consumption, and sustainable economic growth: A novel framework for IEA countries | Khan I.; Hou F.; Zakari A.; Tawiah V.K. | 2021 | Energy | 236 | 59 | Khan et al. (2021) |
| Output, renewable energy consumption and trade in Africa | Ben Aïssa M.S.; Ben Jebli M.; Ben Youssef S. | 2014 | Energy Policy | 227 | 20.64 | Ben Aïssa et al. (2014) |
| Policy for material efficiency – Sustainable taxation as a departure from the throwaway society | Stahel W.R. | 2013 | Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences | 207 | 17.25 | Stahel (2013) |
| Predicted versus observed heat consumption of a low energy multifamily complex in Switzerland based on long-term experimental data | Branco G.; Lachal B.; Gallinelli P.; Weber W. | 2004 | Energy and Buildings | 204 | 9.71 | Branco et al. (2004) |
| Title | Authors | Year | Journal | Total citations | Citations/Year | Reference |
|---|---|---|---|---|---|---|
| Effect of foreign direct investments, economic development and energy consumption on greenhouse gas emissions in developing countries | Sarkodie S.A.; Strezov V. | 2019 | Science of the Total Environment | 942 | 157 | |
| Dynamic life cycle assessment (LCA) of renewable energy technologies | Pehnt M. | 2006 | Renewable Energy | 546 | 28.74 | |
| Fostering a renewable energy technology industry: An international comparison of wind industry policy support mechanisms | Lewis J.I.; Wiser R.H. | 2007 | Energy Policy | 441 | 24.50 | |
| Solar-hydrogen: Environmentally safe fuel for the future | Nowotny J.; Sorrell C.C.; Sheppard L.R.; Bak T. | 2005 | International Journal of Hydrogen Energy | 372 | 18.60 | |
| Limitations of carbon footprint as indicator of environmental sustainability | Laurent A.; Olsen S.I.; Hauschild M.Z. | 2012 | Environmental Science and Technology | 298 | 22.92 | |
| The impact of globalization and financial development on environmental quality: Evidence from selected countries in the Organization for Economic Co-operation and Development (OECD) | Zafar M.W.; Saud S.; Hou F. | 2019 | Environmental Science and Pollution Research | 244 | 40.67 | |
| The dynamic links among energy transitions, energy consumption, and sustainable economic growth: A novel framework for IEA countries | Khan I.; Hou F.; Zakari A.; Tawiah V.K. | 2021 | Energy | 236 | 59 | |
| Output, renewable energy consumption and trade in Africa | Ben Aïssa M.S.; Ben Jebli M.; Ben Youssef S. | 2014 | Energy Policy | 227 | 20.64 | |
| Policy for material efficiency – Sustainable taxation as a departure from the throwaway society | Stahel W.R. | 2013 | Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences | 207 | 17.25 | |
| Predicted versus observed heat consumption of a low energy multifamily complex in Switzerland based on long-term experimental data | Branco G.; Lachal B.; Gallinelli P.; Weber W. | 2004 | Energy and Buildings | 204 | 9.71 |
Overall, the prominence of journals such as Energy Policy, Renewable Energy, Science of the Total Environment, and Environmental Science and Technology confirms the strategic importance of this research domain within global debates on energy and sustainability.
4.4 Analysis of journal citation patterns
Table 2 shows that research on renewable energy technology transfer is concentrated in a limited set of 10 high-impact journals. Energy Policy has the highest number of articles (47) and citations (2,842), supported by strong impact indicators (h-index of 29, g-index of 47). This confirms its position as the primary venue for policy-oriented studies on energy governance and technology dissemination. Renewable Energy ranks second with 32 publications and 1,502 citations, emphasizing the technical and engineering dimensions of renewable systems. Sustainability (Switzerland) contributes 16 articles, while journals such as Energies, Journal of Cleaner Production, and Applied Energy offer complementary coverage of environmental management, efficiency, and clean production practices.
Top 10 high-impact journals
| Rank | Journal | NP | NC | AC | Cites per year | h | g |
|---|---|---|---|---|---|---|---|
| 1 | Energy Policy | 47 | 2,842 | 60.47 | 81.20 | 29 | 47 |
| 2 | Renewable Energy | 32 | 1,502 | 46.94 | 46.94 | 14 | 32 |
| 3 | Sustainability (Switzerland) | 16 | 189 | 11.81 | 17.18 | 8 | 13 |
| 4 | Energies | 15 | 215 | 14.33 | 30.71 | 8 | 14 |
| 5 | Energy | 13 | 921 | 70.85 | 41.86 | 11 | 13 |
| 6 | Energy for Sustainable Development | 8 | 189 | 23.63 | 11.81 | 5 | 8 |
| 7 | Resource, Conservation and Recycling | 8 | 116 | 14.50 | 3.74 | 2 | 8 |
| 8 | Journal of Cleaner Production | 6 | 383 | 63.83 | 42.56 | 6 | 6 |
| 9 | Applied Energy | 6 | 331 | 55.17 | 12.26 | 6 | 6 |
| 10 | Energy Conversion and Management | 6 | 282 | 47.00 | 8.81 | 6 | 6 |
| Rank | Journal | NP | NC | AC | Cites per year | h | g |
|---|---|---|---|---|---|---|---|
| 1 | Energy Policy | 47 | 2,842 | 60.47 | 81.20 | 29 | 47 |
| 2 | Renewable Energy | 32 | 1,502 | 46.94 | 46.94 | 14 | 32 |
| 3 | Sustainability (Switzerland) | 16 | 189 | 11.81 | 17.18 | 8 | 13 |
| 4 | Energies | 15 | 215 | 14.33 | 30.71 | 8 | 14 |
| 5 | Energy | 13 | 921 | 70.85 | 41.86 | 11 | 13 |
| 6 | Energy for Sustainable Development | 8 | 189 | 23.63 | 11.81 | 5 | 8 |
| 7 | Resource, Conservation and Recycling | 8 | 116 | 14.50 | 3.74 | 2 | 8 |
| 8 | Journal of Cleaner Production | 6 | 383 | 63.83 | 42.56 | 6 | 6 |
| 9 | Applied Energy | 6 | 331 | 55.17 | 12.26 | 6 | 6 |
| 10 | Energy Conversion and Management | 6 | 282 | 47.00 | 8.81 | 6 | 6 |
Note(s): NP = number of publications, NC = number of citations, AC = citations per article, h = h-index, g = g-index
These results indicate that while publication outlets are diverse, a small number of high-impact journals dominate the field. Their combined influence demonstrates the dual orientation of technology transfer research: toward policy and governance, and toward technical and environmental innovation.
Figure 4 shows a citation network of key journals related to renewable energy technology transfer, created using VOSviewer. It includes sources cited at least 20 times. Among the 161 sources, 15 meet this criterion and form four separate clusters.
The network displays several clusters of nodes, each represented by circles with labels, connected by thin curved lines. At the center-right of the network, a medium-sized node labeled “energy policy” acts as the main hub. From this node, three lines extend to smaller nodes labeled “energy”, “international journal of energy”, and “energy for sustainable develop”. To the left of the main hub, two curved lines extend toward two nodes labeled “applied energy” and “journal of cleaner production”, which are positioned near each other in the upper-left region and connected by a thin line. Further left, a cluster contains three nodes: “renewable energy”, “energies”, and “sustainability (Switzerland)”. The node labeled “renewable energy” is the largest within this cluster and is linked directly to “energies” below it and to “sustainability (Switzerland)” slightly above it. A long curved line connects “renewable energy” back toward the central hub “energy policy”. The logo for V O S viewer is shown in the lower-left corner.Mapping the network of highly cited sources. Source(s): Created by authors
The network displays several clusters of nodes, each represented by circles with labels, connected by thin curved lines. At the center-right of the network, a medium-sized node labeled “energy policy” acts as the main hub. From this node, three lines extend to smaller nodes labeled “energy”, “international journal of energy”, and “energy for sustainable develop”. To the left of the main hub, two curved lines extend toward two nodes labeled “applied energy” and “journal of cleaner production”, which are positioned near each other in the upper-left region and connected by a thin line. Further left, a cluster contains three nodes: “renewable energy”, “energies”, and “sustainability (Switzerland)”. The node labeled “renewable energy” is the largest within this cluster and is linked directly to “energies” below it and to “sustainability (Switzerland)” slightly above it. A long curved line connects “renewable energy” back toward the central hub “energy policy”. The logo for V O S viewer is shown in the lower-left corner.Mapping the network of highly cited sources. Source(s): Created by authors
The red cluster, led by Renewable Energy with 32 articles, 1,502 citations, and a link strength of 4, primarily focuses on technical and practical research. Meanwhile, the green cluster, centered on Energy Policy with 47 articles, 2,842 citations, and a link strength of 12, is central to debates on energy governance and technology dissemination. The blue cluster features Journal of Cleaner Production (6 articles, 383 citations, link strength 6) and Applied Energy (6 articles, 331 citations, link strength 1), both of which address sustainability and energy optimization. The yellow cluster consists of only Energy (13 articles, 921 citations), an impactful journal that represents a separate thematic focus.
Figure 4 presents a citation network of key renewable energy technology transfer journals via VOSviewer. Overall, the map illustrates how publication sources are organized into thematic clusters with citation linkages across them, suggesting that renewable energy technology transfer research engages a range of disciplinary perspectives rather than being confined to a single domain.
4.5 Top 10 productive countries
Table 3 shows that the United Kingdom (53 publications), China (51), and the United States (47) are the leading contributors to research on renewable energy technology transfer. In terms of impact, the United States has the highest number of citations (2,166), followed by China (1,677) and the United Kingdom (1,590). Australia, with only 18 papers, has the highest average citations per publication (88.1), indicating particularly influential research. Germany, Switzerland, Denmark, India, Italy, and the Netherlands complete the top 10.
Top 10 productive countries
| Country | Citations | Articles | Citations per publication |
|---|---|---|---|
| United States | 2,166 | 47 | 46.09 |
| China | 1,677 | 51 | 32.88 |
| United Kingdom | 1,590 | 53 | 30.00 |
| Australia | 1,586 | 18 | 88.11 |
| Germany | 1,077 | 24 | 44.88 |
| Switzerland | 838 | 12 | 69.83 |
| Denmark | 601 | 11 | 54.64 |
| India | 590 | 21 | 28.10 |
| Italy | 524 | 12 | 43.67 |
| Netherlands | 442 | 16 | 27.63 |
| Country | Citations | Articles | Citations per publication |
|---|---|---|---|
| United States | 2,166 | 47 | 46.09 |
| China | 1,677 | 51 | 32.88 |
| United Kingdom | 1,590 | 53 | 30.00 |
| Australia | 1,586 | 18 | 88.11 |
| Germany | 1,077 | 24 | 44.88 |
| Switzerland | 838 | 12 | 69.83 |
| Denmark | 601 | 11 | 54.64 |
| India | 590 | 21 | 28.10 |
| Italy | 524 | 12 | 43.67 |
| Netherlands | 442 | 16 | 27.63 |
These findings suggest that productivity and influence are concentrated in a small group of countries with strong research infrastructures and policy commitments, while the growing contributions of China and India highlight an expanding global base for knowledge on technology transfer.
Figure 5 shows the citation network for countries with at least five publications and 20 citations, grouped into seven clusters, where links indicate collaboration or citation connections between countries.
The network displays multiple clusters of country nodes, each shown as colored circles with labels and connected by curved lines. Near the center, a large blue node labeled “united kingdom” connects to several nearby nodes, including “Netherlands”, “Switzerland”, “Poland”, “Austria”, and “India”, forming a dense blue cluster. Slightly below and to the left, a red cluster centers on the node labeled “china”, which links to “south korea”, “japan”, and “united states”, creating a group of red interconnected nodes. At the bottom, a green cluster centers on the node labeled “Germany”, which is linked to “Iran”, “south Africa”, and “Spain”, with curved lines. Further right, a yellow-orange cluster has the nodes “Denmark”, “Italy”, “Brazil”, and “France”. In the upper-left corner, a purple cluster includes the nodes “Portugal” and “Australia”, connected by thin lines to the broader network. The logo for “V O S Viewer” is shown on the bottom left.Mapping the network of highly cited countries. Source(s): Created by authors
The network displays multiple clusters of country nodes, each shown as colored circles with labels and connected by curved lines. Near the center, a large blue node labeled “united kingdom” connects to several nearby nodes, including “Netherlands”, “Switzerland”, “Poland”, “Austria”, and “India”, forming a dense blue cluster. Slightly below and to the left, a red cluster centers on the node labeled “china”, which links to “south korea”, “japan”, and “united states”, creating a group of red interconnected nodes. At the bottom, a green cluster centers on the node labeled “Germany”, which is linked to “Iran”, “south Africa”, and “Spain”, with curved lines. Further right, a yellow-orange cluster has the nodes “Denmark”, “Italy”, “Brazil”, and “France”. In the upper-left corner, a purple cluster includes the nodes “Portugal” and “Australia”, connected by thin lines to the broader network. The logo for “V O S Viewer” is shown on the bottom left.Mapping the network of highly cited countries. Source(s): Created by authors
The red cluster, dominated by the United States (9 links and a total link strength (TLS) of 19) and China (8 links, TLS 11), demonstrates substantial cooperation even amid geopolitical tensions (Zhang et al., 2022). The blue cluster centers on the United Kingdom (12 links, TLS 32), the most connected node in the network, owing to its many European partners. Germany leads the green cluster (8 links, TLS 10), connected with Spain, South Africa, and Iran. Denmark is part of the yellow cluster (11 links, TLS 33) and has the highest overall link intensity, highlighting its significant academic influence. The orange cluster comprises only Italy (5 links, TLS 8), which is connected to nearby countries like Germany and the United Kingdom, reflecting modest but regionally integrated cooperation. Australia leads the purple cluster (4 links, TLS 4). Despite Australia’s limited connectivity, it has a high academic influence with a large number of citations. Finally, the light blue cluster is led by Switzerland (10 links, TLS 18). This country serves as an important bridge between clusters, enhancing global connectivity within the citation network.
Figure 5 shows seven clusters of countries publishing on renewable energy technology transfer. The United States, China, and the United Kingdom dominate the network, with European countries linking regional collaborations.
4.6 Citations analysis of authors
Figure 6 maps 412 highly cited authors into seven collaborative clusters. The figure highlights that relatively few scholars shape the intellectual foundation of the field. Ulrich Elmer Hansen, with 146 citations and 11 co-authorship links, and Rasmus Lema, with 141 citations and 18 links, occupy central positions that connect otherwise separate clusters. Frauke Urban, with 127 citations and 24 links, plays a bridging role, facilitating cross-group collaboration. Tobias S. Schmidt is noteworthy for both high citation impact (159 citations) and active network engagement (15 links). Other contributors, such as Joern Huenteler (122 citations), Tania Urmee (128 citations from a single article), and Eric Martinot (92 citations), illustrate the diversity of influence, ranging from focused individual contributions to broader integrative roles.
The network visualization displays multiple clusters of nodes shown as colored circles with author names, connected by curved lines. Near the top center, a yellow cluster forms around the node labeled “urban, frauke”, which is linked to several nearby authors, including “kirchherr, julian”, “martinot, e.”, and “hanlin, rebecca”. Below this cluster, a green set of nodes includes “hansen, ulrich elmer”, “eicke, laima”, “blohmke, julian”, and “garcia, rodrigo”, all connected through multiple curved lines. At the top, an orange node labeled “urmee, tania”, connected downward to the yellow cluster. A teal cluster on the bottom left has the labels “lema rasmus” and “(justin) zhang, zuopeng”. On the right side, a red cluster centers on “huenteler, joern”, which links closely with “chen, yunnan”. A blue node on the top right is labeled “martinot, eric”. On the bottom right, a purple cluster has the label “schmidt, tobias s” and “balachandra, p”. Curved multicolored edges weave through the clusters. A V O S viewer logo appears in the lower left corner.Author collaboration network. Source(s): Created by authors
The network visualization displays multiple clusters of nodes shown as colored circles with author names, connected by curved lines. Near the top center, a yellow cluster forms around the node labeled “urban, frauke”, which is linked to several nearby authors, including “kirchherr, julian”, “martinot, e.”, and “hanlin, rebecca”. Below this cluster, a green set of nodes includes “hansen, ulrich elmer”, “eicke, laima”, “blohmke, julian”, and “garcia, rodrigo”, all connected through multiple curved lines. At the top, an orange node labeled “urmee, tania”, connected downward to the yellow cluster. A teal cluster on the bottom left has the labels “lema rasmus” and “(justin) zhang, zuopeng”. On the right side, a red cluster centers on “huenteler, joern”, which links closely with “chen, yunnan”. A blue node on the top right is labeled “martinot, eric”. On the bottom right, a purple cluster has the label “schmidt, tobias s” and “balachandra, p”. Curved multicolored edges weave through the clusters. A V O S viewer logo appears in the lower left corner.Author collaboration network. Source(s): Created by authors
These patterns indicate that research on renewable energy technology transfer is sustained by a relatively cohesive community in which a handful of highly cited and well-connected authors ensure continuity, collaboration, and cross-fertilization across diverse research perspectives.
Figure 6 shows highly cited authors grouped into seven collaborative clusters. The network reveals that a small group of core scholars plays a central role in shaping research on renewable energy technology transfer.
4.7 Co-occurrence mapping of author keywords
Keyword co-occurrence analysis of the 362 publications identifies six thematic clusters (Figure 7). The green cluster links “renewable energy” with “sustainable development,” “globalization,” “CO2 emissions,” and “foreign direct investment,” reflecting an environmental–economic policy orientation. The red cluster centers on “technology transfer,” “clean development mechanism,” and “technological capabilities,” emphasizing institutional and financial aspects. The yellow cluster highlights country-specific themes, particularly “China,” connected with “energy security,” “trade,” and “innovation.” The blue cluster groups technical terms such as “sustainability,” “solar energy,” and “energy efficiency,” while the purple cluster focuses on “Africa” and “energy policy.” Finally, the light blue cluster associates “energy transition” with “wind energy.” The most frequent keywords are “renewable energy” (100 occurrences), “technology transfer” (47), and “sustainable development” (30), showing the field’s conceptual anchors.
The network visualization displays interconnected clusters of keywords shown as colored circles, linked by curved lines. At the center, the largest green node labeled “renewable energy” connects widely to surrounding terms, including “sustainable development”, “foreign direct investment”, “globalization”, and “c o 2 emissions”. A teal cluster on the left has nodes labeled “energy efficiency”, “solar energy”, “renewables”, and “sustainability”. To the upper right, a yellow node labeled “china” connects to “energy security”, “trade”, and “innovation”. A red cluster toward the top features the node “technology transfer”, linked closely with “clean development mechanism”, “technological capabilities”, “developing countries”, “climate change”, and “c d m”. A purple cluster on the right includes “renewable energy sources”, “energy policy”, and “Africa”, connected by thin curved lines. A blue cluster near the lower right contains “energy transition”, “renewable energies”, and “wind energy”. Multiple multicolored curved links show cross-cluster relationships. The V O S viewer logo appears in the lower left corner.Co-occurrence network of author keywords. Source(s): Created by authors
The network visualization displays interconnected clusters of keywords shown as colored circles, linked by curved lines. At the center, the largest green node labeled “renewable energy” connects widely to surrounding terms, including “sustainable development”, “foreign direct investment”, “globalization”, and “c o 2 emissions”. A teal cluster on the left has nodes labeled “energy efficiency”, “solar energy”, “renewables”, and “sustainability”. To the upper right, a yellow node labeled “china” connects to “energy security”, “trade”, and “innovation”. A red cluster toward the top features the node “technology transfer”, linked closely with “clean development mechanism”, “technological capabilities”, “developing countries”, “climate change”, and “c d m”. A purple cluster on the right includes “renewable energy sources”, “energy policy”, and “Africa”, connected by thin curved lines. A blue cluster near the lower right contains “energy transition”, “renewable energies”, and “wind energy”. Multiple multicolored curved links show cross-cluster relationships. The V O S viewer logo appears in the lower left corner.Co-occurrence network of author keywords. Source(s): Created by authors
Figure 8 illustrates how these themes have evolved over time. Core terms such as “renewable energy,” “technology transfer,” and “sustainable development” were particularly dominant before 2018, while newer topics, including “energy transition,” “energy security,” and “globalization,” have grown rapidly since 2020. This shift from foundational to applied themes has expanded the field from a focus on core concepts to broader policy and innovation issues, with increasing attention to the role of emerging economies in the renewable energy value chain.
The network visualization presents multiple interconnected nodes representing key terms related to renewable energy research. At the center of the network is a large node labeled “renewable energy”, connected by numerous curved lines to surrounding nodes. Directly above it is a node labeled “technology transfer”, which is connected to “China”, “climate change”, “clean development mechanism”, “developing countries”, “technological capabilities”, “solar energy”, and “sustainability”. To the upper right, the node labeled “China” forms a dense cluster of connections on the right, linking to “energy security”, “trade”, “innovation”, “renewable energy sources”, “energy policy”, “Africa”, and “sustainable development”. The lower right of the visualization includes nodes such as “energy transition” and “wind energy”, each linked back to central nodes. To the left of the network, smaller nodes labeled “renewables”, “energy efficiency”, “solar energy”, and “sustainability” are connected by thin lines. Further below, additional nodes such as “foreign direct investment”, “globalization”, and “c o 2 emissions” appear with lighter lines connecting them to the central concepts of “renewable energy” and “sustainable development”. The lines vary in color from shades of blue to green and yellow, reflected in a timeline from 2010 to 2020 as shown in the color legend at the bottom right. The visualization was generated with V O S viewer, indicated by a small logo at the bottom left.Co-occurrence overlay of author keywords. Source(s): Created by authors
The network visualization presents multiple interconnected nodes representing key terms related to renewable energy research. At the center of the network is a large node labeled “renewable energy”, connected by numerous curved lines to surrounding nodes. Directly above it is a node labeled “technology transfer”, which is connected to “China”, “climate change”, “clean development mechanism”, “developing countries”, “technological capabilities”, “solar energy”, and “sustainability”. To the upper right, the node labeled “China” forms a dense cluster of connections on the right, linking to “energy security”, “trade”, “innovation”, “renewable energy sources”, “energy policy”, “Africa”, and “sustainable development”. The lower right of the visualization includes nodes such as “energy transition” and “wind energy”, each linked back to central nodes. To the left of the network, smaller nodes labeled “renewables”, “energy efficiency”, “solar energy”, and “sustainability” are connected by thin lines. Further below, additional nodes such as “foreign direct investment”, “globalization”, and “c o 2 emissions” appear with lighter lines connecting them to the central concepts of “renewable energy” and “sustainable development”. The lines vary in color from shades of blue to green and yellow, reflected in a timeline from 2010 to 2020 as shown in the color legend at the bottom right. The visualization was generated with V O S viewer, indicated by a small logo at the bottom left.Co-occurrence overlay of author keywords. Source(s): Created by authors
Figure 7 shows six keyword clusters from 362 publications. Core terms like renewable energy, technology transfer, and sustainable development highlight the focus on clean energy and global sustainability agendas.
Figure 8 shows how main themes in renewable energy technology transfer have changed over time. Recent studies are placing more focus on energy transition, energy security, and globalization.
5. Discussion
This study employed bibliometric analysis to examine research on renewable energy technology transfer from 1981 to 2025. The results show that the field has expanded rapidly over the past 2 decades and shifted from a narrow technical focus toward policy, institutional, and geopolitical concerns. This confirms earlier findings that renewable energy research in general grew significantly after 2008 (Ahmad et al., 2020) but adds the insight that technology transfer has become a distinct and increasingly central theme in sustainability transitions.
International cooperation emerges as a defining theme. China, the United States, and the United Kingdom dominate both publication output and cross-country cooperation, confirming the findings of Zhang et al. (2022) and Sharma and Sengar (2025). China’s growing academic and industrial engagement reflects its dual role as both a major innovator and a key facilitator of South–South knowledge exchange (Jackson et al., 2021). European countries such as Germany, Denmark, and Switzerland continue to serve as collaborative bridges, while India is emerging as a dynamic contributor linking developed and developing regions (Apeh and Nwulu, 2025).
Institutional readiness plays a crucial role in shaping the outcomes of renewable energy technology transfer. Beyond the acquisition of physical technologies, success depends on how effectively local institutions can absorb, adapt, and apply external knowledge within their own innovation systems. This finding aligns with prior evidence that weak governance and limited institutional capacity can hinder technology diffusion (Lee et al., 2017) and supports recent findings that absorptive capability is a key determinant of renewable energy innovation and efficiency (Fernández, 2025; Wang et al., 2025). Strengthening these institutional foundations can therefore enhance both innovation capacity and the sustainability of technology transfer in emerging economies.
Author collaboration networks further reinforce these themes. Influential researchers such as Ulrich Elmer Hansen, Rasmus Lema, and Frauke Urban play pivotal roles not only in producing highly cited work but also in linking otherwise separate research communities. This reflects a cohesive scholarly structure where a few central figures facilitate dialogue across clusters, consistent with broader patterns observed in climate innovation research (Sharma and Sengar, 2025).
Keyword analysis highlights the evolution of the field’s conceptual boundaries. Earlier bibliometric reviews of renewable energy also identified the growing importance of energy transition and energy security (Ahmad et al., 2020; Sharma and Sengar, 2025). Our findings extend this evidence by showing that these themes increasingly link technology transfer to emerging economies. This marks a significant broadening of the research agenda, from purely technical questions toward the policy, security, and geopolitical contexts that condition technology flows.
The analysis of journals confirms the centrality of Energy Policy and Renewable Energy. In our dataset, Energy Policy had both the largest publication volume and the highest citation count, while Renewable Energy ranked second in output and impact (Table 2). This pattern shows that research on technology transfer is concentrated in outlets that address both governance and technical dimensions of the energy transition. Earlier bibliometric reviews also identified these journals as leading venues for renewable energy research (Ahmad et al., 2020; Sharma and Sengar, 2025). Our results extend this evidence by demonstrating that technology transfer has become a distinct and consistent focus within these journals, underscoring their role in shaping policy debates and technical innovation in the renewable sector.
Overall, this study demonstrates that renewable energy technology transfer has evolved into a multidimensional research domain characterized by international collaboration, institutional capacity, and the increasing participation of emerging economies. Its trajectory illustrates how global policy frameworks, domestic governance, and geopolitical dynamics influence the production and diffusion of knowledge. However, important research gaps remain. Limited attention has been given to domestic diffusion processes, particularly how recipient countries adapt and scale transferred technologies. South–South cooperation, despite its growing relevance for regional sustainability, has also not been systematically examined. Moreover, the connection between technology transfer and the strengthening of local innovation capacity remains underdeveloped, despite its vital importance for resilience and long-term self-reliance. Addressing these gaps would not only advance academic understanding but also provide policymakers and industry leaders with practical insights for accelerating sustainable energy transitions.
6. Conclusion and contributions
This study conducted a bibliometric analysis of 362 articles published in Scopus on renewable energy technology transfer published between 1981 and 2025. By examining publication trends, citation patterns, influential authors and countries, collaboration networks, thematic clusters, and keyword co-occurrence, it provides a systematic overview of the intellectual and regional development of this field.
The analysis yields four principal findings. First, research on renewable energy technology transfer has expanded significantly, underscoring its importance for climate change mitigation, low-carbon development, and innovation in developing regions. Second, the intellectual structure of the field is organized around three thematic clusters: renewable energy, sustainable development, and technology transfer. These are closely associated with international investment, environmental agreements, and the global energy transition.
Third, collaboration networks indicate a cohesive scholarly community in which key researchers play central roles in connecting clusters and advancing interdisciplinary dialogue. Fourth, journals such as Energy Policy and Renewable Energy have established themselves as leading publication venues, shaping both theoretical and policy dimensions of the field.
These findings have significant implications. For policymakers, they emphasize the need to integrate technology transfer into energy transition strategies that align with climate and sustainability objectives. For the industry, they identify opportunities to strengthen partnerships, foster innovation, and expand renewable energy capacity. For scholars, this study provides a comprehensive framework for understanding the dynamics of cross-border knowledge flows and for advancing future research on sustainable energy transitions. By clarifying the intellectual foundations, regional dynamics, and collaborative patterns of renewable energy technology transfer, this study contributes an original and timely perspective to both academic scholarship and policy debate.
7. Limitations and future research
Although research on renewable energy technology transfer has expanded, critical gaps remain. Limited attention has been given to how technologies are adopted and adapted locally, the influence of institutions and policies, and the transfer of technologies between countries in the Global South. Conditions for domestic diffusion and innovation also remain underexplored. Future research should further explore institutional and policy contexts affecting transfer outcomes. The roles of international organizations, climate finance, and multisectoral partnerships also merit further investigation.
This study used Scopus as the main data source because of its wide coverage and reliable citation records. Relying on a single database, however, may limit the scope. Studies indexed in Web of Science, Dimensions, or OpenAlex, particularl y those from developing regions or written in other languages, might not have been captured. The focus on peer-reviewed journal papers also excluded reports and conference works that may contain useful findings. The selected keywords were quite specific, so some related themes may have been overlooked. Future research could combine multiple databases, expand keyword searches, and complement bibliometric analysis with qualitative or case-based evidence to provide a broader understanding of renewable energy technology transfer and its policy implications.
Declaration of generative AI use and AI assistance
During the preparation of this manuscript, the authors used ChatGPT to assist with correcting grammar and typos and also engaged a professional English editing service for proofreading. All research design, analysis, and interpretation were conducted by the authors, who accept full responsibility for the content.

