Ge Hu
Ziteng Xu
Weimin Chen- 1Shenzhen Audencia Financial Technology Institute, Shenzhen University, Shenzhen, China
- 2School of Business, Hunan University of Science and Technology, Xiangtan, China
As Environmental, Social, and Governance (ESG) principles gain global traction, greenwashing has emerged as a significant challenge, undermining sustainable development and eroding trust in capital markets. This study provides a systematic review of ESG greenwashing research in both English and Chinese literature, conducting a bibliometric analysis of 652 papers published between 2017 and 2025. These papers were sourced from the Web of Science Core Collection and CNKI databases, using CiteSpace for visualization. The research timeline reveals three phases: the emerging phase (2017—2021), the growth phase (2022–2023), and the expansion phase (2024—2025), showing a consistent rise in research activity. Co-occurrence and clustering analyses of keywords reveal that English-language literature predominantly addresses green marketing, corporate social responsibility, and legitimacy, while Chinese-language research, emerging later, focuses on practical issues such as financing constraints, green finance, information disclosure, and collaborative governance. Future research should focus on AI governance, firm perception of institutional pressures, executive characteristics, and the coordination of policy instruments to address ESG greenwashing.
1 Introduction
The concept of Environmental, Social, and Governance (ESG) was first introduced in the 2004 United Nations Global Compact report Who Cares Wins, which highlighted how non-financial factors—environmental, social, and governance dimensions—could be integrated into investment analysis and corporate strategy as critical variables. In recent years, global challenges such as climate change, social inequality, and corporate governance failures have propelled ESG from a marginal concept to a mainstream investment paradigm.
According to data from the Wind database, the number of global signatories to the United Nations Principles for Responsible Investment (UNPRI) has rapidly increased since 2017, reaching 5,122 institutions by September 30, 2025, including 128 signatories from China. During the same period, the number of asset owner signatories has also steadily grown, reflecting the expanding institutionalization and global acceptance of ESG-focused investment practices. Even during the 2020 market sell-off triggered by the COVID-19 pandemic, global sustainable funds saw a net inflow of USD 45.6 billion in the first quarter, while the overall fund industry experienced net outflows of USD 384.7 billion. This contrast underscores the resilience and appeal of ESG investments. The UNPRI signatory data cited in this paper is sourced from the Wind Financial Database, a leading financial data service platform in China. The specific retrieval process is as follows: open the new version of EDB, navigate to the ESG macro section under the Securities Market allocation, where the UNPRI signatory statistical data series can be found. This data is recorded monthly. The Wind database aggregates and updates authoritative data from public sources such as the official UNPRI website. To analyze, this study uses the data series integrated by the Wind platform.
However, alongside its growing prominence, ESG has also given rise to performative practices that undermine the credibility of sustainable finance. Among these, greenwashing—the deliberate exaggeration or misrepresentation of corporate sustainability performance—has become the most pervasive and controversial form (Xiao, 2024). The term “greenwashing,” coined by environmentalist Jay Westerveld in 1986, originally referred to companies overstating their environmental commitments to cover up shortcomings in their actual practices. In the ESG context, greenwashing refers to any behavior that misleads the public into forming an overly positive view of an organization’s environmental performance, practices, or products (Lyon and Montgomery, 2015). Companies often engage in greenwashing by selectively disclosing favorable information or manipulating disclosures to overstate their actual performance, misleading investors and the public (Huang, 2025). In China, the lack of unified ESG disclosure standards, weak regulatory oversight, limited penalties for misconduct, and persistent information asymmetry further incentivize firms to engage in greenwashing for short-term gains. Such practices can create a “crowding-out effect,” where opportunistic firms undermine genuinely sustainable ones in capital markets.
A substantial body of bibliometric research has emerged in the field of ESG, mapping its knowledge structure, theoretical frameworks, and measurement systems, while tracing its evolution in corporate governance, information disclosure, and green transformation. Li et al. (2021) conducted a comprehensive visual bibliometric analysis of 593 articles published in “UTD24” top-tier journals indexed in the Web of Science database using CiteSpace. Their study systematically reviewed the research hotspots, theoretical frameworks, economic consequences, and measurement approaches in the ESG domain, providing an integrative overview of the field from 2004, when the ESG concept was formally introduced to 2021. Additionally, they identified emerging trends and research gaps, offering potential directions for future research. Khan (2022) analyzed 199 core articles published between 2012 and 2020 from the Scopus database, employing VOSviewer for Bibliometric analyses. His study focused on three key research streams: (1) the relationship between corporate characteristics and ESG performance, (2) the link between corporate governance and ESG performance, and (3) the financial materiality of ESG disclosure. Forliano et al. (2025) conducted a systematic review of the greenwashing research by analyzing studies published between 2003 and 2023 in the Scopus and Web of Science databases using the Bibliomatrix package in R and VOSviewer. Their research identified four major clusters—symbolic management, environmental regulation, corporate performance, and perception of impact—and developed a multi-level theoretical framework integrating macro-, meso-, and micro-level perspectives. This framework provides a structured lens for understanding of corporate greenwashing behavior. Galletta et al. (2024) combined the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach with bibliometric analysis to investigate greenwashing phenomena in the banking sector. Their findings revealed a paradox: under pressure to meet ESG objectives, banks often construct a “green” image by overstating environmental commitments rather than taking substantive actions. Such practices erode consumer trust and hinder progress toward sustainable finance. The authors call for future research on developing standardized disclosure frameworks, strengthening regulatory oversight, and exploring the role of financial technology in enhancing transparency to shift the banking industry from greenwashing to genuine green transformation. Trotta et al. (2024) used VOSviewer and the Bibliometrix package in R to conduct a bibliometric analysis of literature on FinTech and ESG published between 2017 and 2023. Their findings indicate that research at the intersection of FinTech and ESG remains in its infancy, with a limited and fragmented body of literature. Studies focusing on the social dimension are particularly underrepresented.
In recent years, bibliometric studies in the field of ESG have primarily focused on the overall development trajectory, knowledge structure, and the role of ESG in corporate governance and sustainable development. These studies have provided a systematic perspective for understanding the academic progress and evolution within the ESG domain, contributing to the ongoing refinement of its theoretical framework. However, bibliometric reviews specifically addressing ESG greenwashing are notably scarce, and no comparative analyses have been conducted between English-language and Chinese-language literature. In response, this study systematically reviews and synthesizes the research on ESG greenwashing published since 2017, aiming to identify key research hotspots, emerging trends, and developmental trajectories in this field. Using the CiteSpace visualization tool, this study presents a visual analysis of the thematic focuses and evolutionary pathways of ESG greenwashing research, offering valuable insights for future academic inquiry and policy development. A comprehensive exploration of the research trajectory and trends in ESG greenwashing has significant theoretical and practical implications for enhancing information disclosure mechanisms, improving corporate sustainable governance, and advancing sustainable development.
The paper is structured as follows. Section 1 provides the introduction. Section 2 outlines the data source and research methods. Section 3 presents the main visualization results. Section 4 discusses the research hotspots identified in both English- and Chinese-language literature. Section 5 reviews strategies proposed by scholars to address ESG greenwashing. Finally, Section 6 concludes the paper, highlights its limitations, and offers recommendations for future research and policy development.
2 Materials and methods
2.1 Data source and search strategy
As research on ESG greenwashing was still in its early stages prior to 2017, with limited and fragmented studies, this study defines the retrieval period from January 1, 2017, to September 15, 2025, to ensure comprehensive coverage and representativeness of the collected literature.
This study defines the research period from January 1, 2017, to September 15, 2025, based on both conceptual and practical considerations, marking 2017 as a critical inflection point in ESG greenwashing research.
Conceptually, 2017 represents a pivotal shift in which ESG transitioned from a niche concept to a mainstream investment paradigm. This transformation is evident in the significant increase in signatories to the United Nations Principles for Responsible Investment (UNPRI) from that year onward, as discussed in our Introduction. This mainstreaming of ESG heightened scrutiny of corporate sustainability claims, elevating “greenwashing” as a central and sharply defined research issue within the ESG context, distinct from earlier, more fragmented discussions of general corporate environmentalism or CSR communication.
Practically, prior to 2017, the specific intersection of “ESG” and “greenwashing” was rarely explored in the academic literature, as confirmed by our preliminary searches. By focusing on this timeframe, we can conduct a more coherent and focused bibliometric analysis of the emergent research field as it has evolved. While we acknowledge that excluding earlier studies on greenwashing in broader contexts (e.g., general environmental marketing) may limit the perspective on the long-term evolution of the concept, our primary aim is to map the knowledge structure of ESG-specific greenwashing research, which solidified as a distinct field around this period.
Thus, the selection of this timeframe ensures both the analytical coherence and the representativeness of the literature sample for investigating the contemporary research landscape of ESG greenwashing.
International literature was retrieved from the Web of Science Core Collection database, with document types restricted to Articles, Review Articles, and Early Access publications, and language limited to English. The data sources include SCI-EXPANDED, SSCI, and A&HCI indexes. During the literature retrieval process, all categories from the Web of Science Categories were selected. An initial search yielded 543 records, of which 471 valid publications were retained after manual screening and relevance verification.
Chinese-language literature was obtained from the China National Knowledge Infrastructure (CNKI) database. Due to the limited number of related studies, no journal restrictions (e.g., CSSCI or Peking University Core Journals) were imposed. The initial search produced 224 journal articles, and after excluding irrelevant or duplicate records through manual review, 181 valid documents were included in the analysis.
The English and Chinese search terms used in this study are summarized in Table 1. “TS” stands for “Topics.” All retrieved publications were organized and managed using Zotero 7, while CiteSpace 6.3.1 was employed for bibliometric and visualization analyses.
Table 1. Search terms for ESG greenwashing in English and Chinese.
Through a search of relevant ESG greenwashing literature on CNKI, we found that related studies only began to appear in 2021, with no Chinese-language literature available prior to 2017, making a literature review for this period impossible. Using the same search query, we identified 41 relevant studies in the Web of Science database. The review of key English-language published before 2017 will be included in the Discussion section.
2.2 Inclusion and exclusion criteria
2.2.1 Inclusion criteria
1. The research focuses on ESG greenwashing or related issues;
2. The study is an original research article or a review paper;
3. The literature is in either English or Chinese.
2.2.2 Exclusion criteria
1. Studies unrelated to ESG greenwashing;
2. Duplicate publications, especially those of the same study published in different journals or platforms;
3. Non-English or non-Chinese literature, or articles published in non-academic journals.
The literature selection process was conducted independently by the first and second authors based on the above criteria. In case of disagreements, the corresponding author made the final decision or resolved the issue through joint discussion.
2.3 Statistical analysis
This study used CiteSpace 6.3.1 for data processing, visualization, and network analysis. The time span was set from 2017 to 2025, with one-year intervals. The g-index is an important selection criterion in CiteSpace. It calculates a modified g-index for each slice and adjusts the network size through the incremental ratio parameter, k. The larger the value of k, the bigger the network, and the denser the nodes become. A commonly used and reasonable choice for k is 25, which is the default value in CiteSpace and is widely applied in bibliometric studies. For instance, Niu et al. (2025) used CiteSpace to analyze the evolution and trends of research hotspots in medical large language models, setting k to 25. In this study, due to the large number of English-language literature, we set k to 23 in order to highlight the key nodes, while the default value of 25 was applied to the Chinese-language literature. CiteSpace provides two pruning methods for network simplification: Pathfinder and Minimum Spanning Tree (MST). Pathfinder helps to simplify the network and highlight its important structural features, with the advantage of completeness (a unique solution). On the other hand, MST is more efficient and provides quick results. To avoid cluttered and difficult-to-interpret visualizations, we applied Pathfinder and pruning to the merged network during the pruning process (Chen et al., 2015). The analysis included publication volume statistics, keyword co-occurrence, keyword clustering, and keyword burst detection, with all results visualized. Keyword burst detection tables were constructed to identify the evolutionary pathways and developmental trends of research hotspots, providing valuable insights into future directions for ESG greenwashing research. Additionally, Microsoft Excel 2023 was used for basic descriptive statistics, including annual publication counts and keyword frequency analysis.
The literature retrieval, selection, and visualization process, conducted in accordance with PRISMA guidelines for systematic reviews, is illustrated in Figure 1.
Figure 1. PRISMA flowchart.
3 Results
3.1 Annual publication volume analysis
Figure 2 shows the annual distribution of publications on ESG greenwashing research from 2017 to 2025. As of September 15, 2025, a total of 652 relevant publications were identified, including 471 in English and 181 in Chinese. Overall, research interest in this field has steadily increased, with the number of English-language publications consistently outpacing Chinese-language ones. This trend reflects higher international engagement and academic activity within the global research community. Based on the annual distribution, the development of ESG greenwashing research can be broadly categorized into three stages: the emergence stage (2017—2021), the growth stage (2022—2023), and the expansion stage (2024—2025).
Figure 2. Annual distribution of publications on ESG greenwashing research (2017—2025).
During the emergence stage (2017—2021), the annual publication volume remained low and stable, with no relevant studies identified in Chinese-language literature. This period marks the initial exploratory phase of ESG greenwashing research, predominantly represented in English-language publications. Studies during this stage focused on topics such as green marketing strategies, corporate legitimacy, and sustainable image management, reflecting early efforts to evaluate and question corporate environmental responsibility.
In the growth stage (2022—2023), the number of publications increased significantly in both Chinese- and English-language literature, and ESG greenwashing gradually became a key subfield of sustainable development and corporate governance research. English-language studies during this stage expanded to cover areas such as corporate social responsibility (CSR) and sustainable finance, emphasizing the connections among greenwashing, investment decisions, and reputational risks. Meanwhile, Chinese-language studies began to explore themes like ESG assurance, green finance, and transition finance, shifting the research focus from policy advocacy to market mechanisms and governance structure. This transition indicated progress in both theoretical inquiry and practical application.
Since 2024, the field has entered the expansion stage (2024—2025), marked by a dramatic surge in publications, especially in English-language research. Between January 1 and September 15, 2025, the number of English-language studies alone surpassed the total output from 2017 to 2023, signaling an unprecedented wave of scholarly attention. This surge coincides with the enactment of the EU Regulation on Environmental, Social, and Governance (ESG) Rating Activities on December 12, 2024, which enhanced the consistency, transparency, and comparability of ESG ratings within the European Union, further stimulating academic interest in the identification and governance of greenwashing.
At this stage, English-language research has taken a distinct technological innovation approach, shifting from traditional textual and case-based analyses to AI-driven detection and satellite remote-sensing verification. These advancements enable more objective measurement and real-time monitoring of corporate greenwashing behavior. Meanwhile, Chinese-language studies, driven by policy initiatives and practical needs, have increasingly focused on transition finance, precision governance tools, and regulatory optimization, gradually forming a more comprehensive research framework that spans conceptual clarification, empirical validation, and policy design.
Overall, from 2017 to 2025, ESG greenwashing research has followed an evolutionary trajectory of “theoretical emergence—academic consolidation—cross-disciplinary innovation.” This progression reflects the academic community’s deepening understanding of corporate sustainability responsibility and the continuous evolution of research methodologies. As global attention on ESG continues to rise, research enthusiasm is expected to intensify, with ESG greenwashing likely to become a central theme in future studies on sustainable development and green governance.
It should be noted that the division of the “greenwashing” research literature into development stages (emergence stage, growth stage, expansion stage) in this study is primarily based on descriptive analysis of annual publication trends and the evolution of keyword themes, rather than formal statistical tests for validation. This stage classification method is commonly used in bibliometric studies and aims to provide a conceptual framework for understanding the development trajectory of the field. However, the boundaries of these stages involve a degree of subjective judgment. Future research could employ more advanced statistical methods to achieve a more precise identification of these development stages.
3.2 Thematic analysis of research hotspots
3.2.1 Keyword co-occurrence analysis
Keyword co-occurrence analysis is a crucial method for identifying research hotspots and tracking the evolution of a field. In this study, CiteSpace was used to construct a keyword co-occurrence network, revealing the structural relationships and developmental trajectories of ESG greenwashing research from a macro-level perspective. The co-occurrence network of keywords in English-language literature is shown in Figure 3A, while the co-occurrence network of keywords in Chinese-language literature is shown in Figure 3B.
Figure 3. Keyword co-occurrence map. (A) English. (B) Chinese.
Generally, higher keyword frequency indicates greater scholarly attention and significance within the research domain, while betweenness centrality measures the extent to which a keyword connects different clusters. Keywords with a centrality value above 0.1 are typically considered highly influential (Yin and Gao, 2025). To provide a more comprehensive evaluation, this study follows the approach of Zhang and Huang (2022), using a composite index (frequency × betweenness centrality) to rank keywords in descending order, and selects the top ten keywords for further analysis (Tables 2, 3).
Table 2. Top 10 keywords related to ESG greenwashing in English-language research.
Table 3. Top 10 keywords related to ESG greenwashing in Chinese-language research Chinese keywords.
For the Web of Science (WoS) dataset, the most frequent keywords include environmental performance, corporate social responsibility (CSR), disclosure, impact, trust, company, sustainability, management, and environmental disclosure. These terms collectively represent the core research hotspots and conceptual foundations of English-language ESG greenwashing studies.
In contrast, the China National Knowledge Infrastructure (CNKI) dataset reveals a distinct research focus. High-frequency keywords in the Chinese-language literature include greenwashing, information disclosure, greenwashing behavior, governance, social responsibility, financing constraints, corporate governance, green innovation, and green finance. This pattern suggests that Chinese research on ESG greenwashing places more emphasis on corporate behavioral regulation, financial support mechanisms, and governance practices, reflecting a more application-oriented and policy-driven approach compared with English-language studies.
3.2.2 Keyword clustering analysis
Keyword clustering, derived from the keyword co-occurrence network, identifies groups of semantically related terms within large-scale textual data. This method allows researchers to delineate the structural composition of research themes and uncover their intrinsic relationships and evolutionary patterns.
CiteSpace evaluates clustering quality using two key parameters: the modularity (Q) value and the silhouette (S) value. A Q value greater than 0.3 indicates a significant clustering structure, while an S value greater than 0.7 suggests efficient and convincing results. Using the log-likelihood ratio (LLR) algorithm, this study conducted keyword clustering for both English and Chinese datasets, with corresponding visualizations presented in Figure 4.
Figure 4. Keyword clustering map. (A) English. (B) Chinese.
For the English-language literature, the clustering results yielded a Q value of 0.7288 (>0.3) and an average S value of 0.9006 (>0.7), indicating high validity and reliability (Figure 4A). For the Chinese-language literature, the Q value reached 0.839 (>0.3) and the S value was 0.9583 (>0.7), further confirming the robustness of the clustering (Figure 4B).
The visualization results show that English-language literature forms 16 major clusters, while Chinese-language literature consists of 6 primary clusters, as summarized in Table 4. International studies primarily focus on themes such as environmental disclosure, corporate sustainability, and ESG performance, integrating multidimensional topics like greenwashing behavior, corporate social responsibility (CSR), artificial intelligence, and consumer behavior. These clusters collectively form an interdisciplinary and integrated research landscape.
Table 4. Comparison of keyword clusters on ESG greenwashing between Chinese and international literature.
In contrast, Chinese-language literature centers on financing constraints, greenwashing, information disclosure, governance, green finance, and audit collaboration. Overall, international studies demonstrate trends toward systematization, integration, and frontier innovation, while Chinese studies are characterized by topic concentration and a more practice-oriented approach.
3.3 Research frontier analysis
With the rapid expansion of research on ESG greenwashing, tracking emerging themes and dynamic trends has become increasingly complex. Keyword burst analysis, a valuable tool for identifying research frontiers, effectively captures sudden increases in scholarly attention to specific themes over time. This method allows researchers to trace the evolutionary trajectory of a discipline and pinpoint its emerging topics (Chen, 2006). In this study, the intensity of keyword bursts was used to visualize the evolution and development of ESG greenwashing research hotspots.
Figure 5A presents the top 20 keywords with the highest burst strength in the English-language literature. A higher burst strength indicates greater representation of emerging research frontiers, with the red segments in the burst bars denoting the active periods of the corresponding keywords.
Figure 5. Top 20 keyword bursts in ESG greenwashing research. (A) English. (B) Chinese.
During the early stage (2017—2019), international research on ESG greenwashing primarily focused on corporate management strategies and green marketing in response to climate change. Keywords such as management, climate change, and green marketing highlight the initial exploration of how companies convert environmental pressures into market opportunities.
In the middle stage (2020—2022), the emergence of keywords like determinants, disclosure, corporate sustainability, sustainable finance, quality, and legitimacy marked a shift toward examining the driving forces behind sustainable development, the quality of ESG information disclosure, and the institutionalization of corporate sustainability and legitimacy.
In the recent stage (2023—2025), high-intensity burst keywords, such as ESG, financial performance, moderating role, incentives, panel data, and markets, indicate that the field has entered an empirical deepening phase. Current studies increasingly explore causal mechanisms linking ESG and financial performance, focusing on moderating effects and the efficacy of market incentive policies. The use of panel data models and other econometric techniques has strengthened the empirical validation of these relationships.
In contrast, while Chinese research on ESG greenwashing started later, it has expanded rapidly with a distinct policy orientation and a focus on risk prevention. According to the keyword burst analysis (Figure 5B), Chinese studies primarily cluster around three major themes: (1) Green finance and the transition of carbon-intensive industries, (2) Information disclosure and compliance mechanisms, and (3) Risk governance and supervisory responses.
In the green finance and industrial transition area, keywords like transition finance, green finance, targeted classification, and petrochemical industry reflect growing attention to the mechanisms linking financial resource allocation with emission reduction during industrial restructuring. This aligns closely with China’s “dual carbon” goals—carbon peaking and carbon neutrality.
Regarding information disclosure and compliance, the emergence of keywords such as assurance, disclosure, standard system, and fiduciary duty reflects efforts to establish an ESG disclosure framework suited to China’s institutional context and to reinforce fiduciary responsibilities within market institutions. These measures aim to curb greenwashing at its institutional source and enhance investor confidence in capital markets.
At the level of risk governance and supervision, the clustering of keywords such as greenwashing risk, identification, anti-greenwashing, law enforcement, and collaborative supervision highlights a growing focus on identifying and controlling greenwashing risks, managing reputational and financial risks, and constructing a multi-stakeholder governance framework that integrates ex-ante warning, interim intervention, and ex-post enforcement.
4 Discussion
This study adopts a bibliometric approach grounded in keyword clustering. Drawing on Table 4 and Figures 4A,B, it systematically maps the thematic structure of research on ESG greenwashing. By comparing the clustering structures and thematic distributions across Chinese and international corpora, the study identifies both divergences and convergences in research hotspots. These comparisons help trace the latent linkages among themes, elucidate the field’s intellectual landscape, clarify its developmental trajectory, and highlight emerging research frontiers. Simultaneously, this paper consolidates the governance strategies for ESG greenwashing proposed in the academic literature, offering theoretical support and practical insights for addressing ESG greenwashing in practice and informing policy development. It should be noted that the literature review in the Discussion section has a descriptive nature.
4.1 Analysis of English-language research hotspots
4.1.1 Motivations for ESG disclosure and their implications for corporate sustainability
Corporate motivations for ESG disclosure are shaped by both managerial incentives and external pressures. At the managerial level, career concerns are a significant internal driver. CEOs may strategically use CSR disclosures to signal their competence and credibility to the market, thus safeguarding their professional reputation and enhancing career progression (Chen et al., 2023). A strong CSR reputation can also facilitate career mobility and improve job transition opportunities (Dai et al., 2023).
At the institutional and market levels, firms’ disclosure decisions are influenced by regulatory conditions, investor expectations, and market competition. Delmas and Burbano (2011) argue that a lax regulatory environment may inadvertently encourage corporate greenwashing. On the other hand, increasing investor and consumer focus on ESG performance pressures firms to improve their disclosure practices to sustain market legitimacy. Dhaliwal et al. (2011) identify financing demand as a critical economic driver: firms with higher ex ante equity costs are more likely to voluntarily disclose ESG information, while high-quality social performance, coupled with transparency can reduce financing costs. Similarly, Reverte (2009) emphasizes that external legitimacy and public pressure—especially media scrutiny—are significant drivers of CSR disclosure. Additionally, factors such as firm size and industry environmental sensitivity play a key role in influencing the quality of ESG disclosure.
The impact of ESG disclosure on corporate sustainability is both multifaceted and ambivalent. While transparent disclosure can generate long-term value, opportunistic practices often carry considerable risks. On the positive side, high-quality disclosure reduces information asymmetry, enhances transparency, and improves market credibility, fostering an environment conducive to sustainable growth. An et al. (2025) demonstrate that ESG disclosure significantly boosts firm value in China by alleviating financing constraints, with stronger effects observed in non-state-owned enterprises, low-pollution industries, and high-transparency firms.
In contrast, opportunistic disclosure—commonly referred to as greenwashing—may offer short-term benefits but poses long-term risks. Wang et al. (2024) show that greenwashing can temporarily improve a firm’s regulatory compliance image and access to credit, but it ultimately leads to higher debt accumulation and financing inefficiency, undermining sustainable performance. Zhou et al. (2024) further argue that greenwashing in environmental disclosure not only diminishes firm value but also erodes market trust, neutralizing any positive impact of environmental information.
Yu et al. (2020) conducted a study based on data from 1,025 large non-financial firms across 47 countries from 2012 to 2016, and developed a comprehensive greenwashing score model. The study found that corporate governance factors (such as the proportion of institutional investors and independent directors), institutional factors (such as reduced corruption levels), and cross-listing significantly mitigate greenwashing behaviors. This research provides important empirical evidence for understanding the mechanisms influencing the quality of ESG disclosures. Wu et al. (2020) analyzed corporate greenwashing behaviors in ESG disclosures and their impact on social welfare by constructing a game theory model. The study revealed that increasing information transparency can help mitigate greenwashing and enhance welfare. However, the relationship between transparency and welfare is not linear. In the medium transparency range, further increasing transparency may lead socially responsible firms to over-invest in observable activities, ultimately reducing welfare. This non-monotonic relationship underscores the importance of tailored regulatory approaches. Policymakers should, therefore, design differentiated policies that account for the current level of transparency, avoiding a “one-size-fits-all” approach. Kim and Lyon (2015) conducted an empirical study on the U. S. electric power industry, focusing on 54 investor-owned electric utilities participating in the U. S. Department of Energy’s (DOE) voluntary greenhouse gas reporting program from 1995 to 2003, with a total of 396 firm-year observations. The study found that corporate environmental information disclosure is a dynamic strategic choice rather than a one-way instance of greenwashing. Companies tend to seek legitimacy during periods of growth, but under shareholder pressure, they may shift to “brownwashing” to conceal costs. External oversight was identified as a key mechanism in curbing both behaviors. However, the study’s sample is limited to the electric power industry, which calls into question the generalizability of its conclusions, and it does not address the impact of other stakeholders, such as consumers. Mitchell and Dino (2011) analyzed multinational panel data from 4,750 publicly listed companies across 45 countries (2004–2007) using a multilevel linear model (HLM). The study found that companies with more severe environmental damage tend to disclose less information selectively. This effect is more pronounced in countries with higher densities of environmental NGOs, stronger protection of civil liberties, and higher levels of globalization, as well as in companies listed abroad. The suppression effect is primarily attributed to companies increasing substantive disclosures rather than reducing symbolic ones. However, the study’s limitation lies in its sample, which is restricted to large publicly listed companies and does not include private enterprises.
In summary, while opportunistic disclosure may temporarily align with compliance and market demands, it ultimately undermines long-term corporate sustainability. The short-term benefits of greenwashing—such as improved regulatory compliance and market image—are offset by long-term drawbacks, including increased financing costs, diminished corporate value, and hindered progress toward genuine sustainable development. This emphasizes the need for more effective, nuanced approaches to ESG disclosure that balance transparency with the potential for greenwashing.
4.1.2 Applications and challenges of artificial intelligence and emerging technologies in ESG greenwashing governance
The rapid advancement of artificial intelligence (AI) and other emerging technologies is reshaping traditional approaches to identifying and governing ESG greenwashing. Empirical research has begun to demonstrate the potential of AI technologies in helping to mitigate corporate greenwashing behaviors. Tian and Shi (2025) found that AI adoption has particularly strong inhibitory effects among non-state-owned enterprises, large firms, and high-polluting industries. Three main factors explain this pattern: first, non-state-owned enterprises, with more flexible decision-making processes, are quicker to adopt AI tools; second, large firms, with abundant resources and technological capabilities, are better positioned to integrate AI into environmental management; third, highly polluting industries, facing stringent regulatory scrutiny and public pressure, have a more pressing need for AI-based governance tools.
At the technological application level, breakthroughs in generative AI and natural language processing (NLP) have opened new frontiers for ESG greenwashing research. Wang (2025) employed ChatGPT-4 to analyze firms’ 10-K annual reports, pioneering the use of generative AI to test ESG lag effects and evaluate ESG rating quality. From an information economics perspective, the study identified herding behavior and greenwashing as key mechanisms underlying rating delays. Thimm and Rasmussen (2024) also utilized ChatGPT to detect Green Image Damaging (GID) information, demonstrating the feasibility of generative AI for environmental text mining and uncovering a surprising finding: firms associated with GID tend to be larger and have higher ESG scores.
Khan et al. (2024) argue that AI mitigates greenwashing through three mechanisms: (1) enhancing transparency via real-time data monitoring, (2) reducing information asymmetry through third-party data verification, and (3) optimizing decision-making through data-driven environmental innovation. Empirical evidence further shows that non-state-owned enterprises, driven by market competition, are more proactive in adopting AI to improve performance, while state-owned enterprises (SOEs)—constrained by political objectives and bureaucratic structures—show more limited governance outcomes. In certain central SOEs, AI has even been misused to obscure environmental violations.
Beyond digital monitoring, the integration of physical verification technologies, such as satellite remote sensing, represents a transition toward multi-source ESG verification. Gu et al. (2023) proposed the concept of “Audit 4.0,” a framework that integrates big data, remote sensing, and the Internet of Things (IoT) to obtain direct evidence from the physical world. This enables real-time, precise, and automated assurance of ESG reports. Compared with traditional ESG assurance, Audit 4.0 offers significant advantages in data completeness, continuous monitoring, instant alerts, and cost efficiency, marking a paradigm shift from declarative to evidence-based ESG verification. Within the broader context of technology-empowered governance, Audit 4.0 has emerged as a key tool for identifying and deterring greenwashing behaviors.
Similarly, FinTech applications have contributed to detecting and deterring greenwashing. Zhou and Wang (2024) examined the interplay between financial technology and sustainable finance, finding that FinTech tools effectively detect greenwashing and limit financial resource allocation to non-compliant firms. Similarly, Qian et al. (2025) demonstrated that banking FinTech significantly curtails corporate greenwashing and promotes substantive rather than strategic green innovation.
However, the rise of AI-driven governance also raises ethical and regulatory concerns. Seele and Schultz (2022) introduced the concept of “machine washing,” referring to deceptive or misleading behaviors in AI that obscure ethical issues through textual, visual, or algorithmic manipulation. They identify six manifestations of this phenomenon: textual misrepresentation, visual manipulation, information omission, algorithmic bias, symbolic compliance, and lobbying activities. This highlights the need for stronger ethical guidelines, algorithmic transparency, and regulatory oversight to ensure that technological progress enhances—rather than undermines—ESG integrity. Safeguarding the authenticity, accountability, and compliance of AI applications is crucial to prevent emerging technologies from becoming tools for greenwashing.
4.1.3 Effects of corporate structure and executive characteristic on greenwashing
Recent international research has extensively examined the relationship between executive characteristics and corporate greenwashing, though findings remain inconclusive. Using data from European non-financial listed firms (2020–2023), Fleitas-Castillo et al. (2025) provide the first evidence of an inverted U-shaped relationship between the proportion of female directors and the level of greenwashing. The strongest deterrent effect is observed when women occupy approximately 40% of board seats.
The concept of brownwashing—where firms underreport negative ESG information or conceal poor performance—contrasts with greenwashing. Extending this distinction, Eliwa et al. (2023) find that female directors primarily curb greenwashing through ethical orientation, while their influence on brownwashing is negligible. Furthermore, the ethical governance effect of female directors is moderated by religious cultural contexts, which tend to weaken its strength. These findings support gender quota policies and highlight the importance of context-sensitive anti-greenwashing strategies that consider cultural diversity.
Beyond gender, other board and top management team (TMT) characteristics also influence greenwashing behavior. Surprisingly, functional diversity within the TMT does not necessarily reduce greenwashing and may, in certain cases, even exacerbate it (Chen and Dagestani, 2023). Hou and Jin (2025) report that higher executive educational attainment improves the quality of ESG disclosure, but disciplinary background plays a critical role. Firms with a larger proportion of executives trained in the humanities tend to be more prone to greenwashing. This finding refines managerial selection criteria and warns against the “elite trap” in ESG reporting, where formal credentials may mask ethical or governance shortcomings.
Regarding compensation and power structures, unbalanced incentive schemes can create new agency problems. Li and Chen (2024) demonstrate that a wider executive pay gap increases corporate risk-taking and significantly raises the likelihood of greenwashing, especially in environments with low environmental awareness, widespread earnings management, severe financing constraints, and weak external oversight. In a complementary study, Zhao et al. (2024) find that power imbalances within the executive team foster decision monopolies, reduce transparency, and weaken regulatory enforcement, thereby facilitating greenwashing. These effects are particularly pronounced in non-state-owned firms, high-marketization regions, and financially constrained enterprises. Together, these studies highlight that misaligned incentives and concentrated power structures can act as structural enablers of greenwashing.
Recent research has also focused on team stability and leader-specific attributes. Deng et al. (2025) show that greater TMT stability significantly suppresses greenwashing, addressing a gap in previous studies that overly emphasized individual-level characteristics. However, evidence regarding celebrity leadership remains mixed. Cao et al. (2025) argue that celebrity CEOs are more likely to engage in greenwashing, particularly during the first 2 years after receiving awards, as increased media attention fuels opportunistic behavior. In contrast, Song and Chen (2025) find that celebrity status reduces greenwashing, suggesting that firms may leverage such reputations to strengthen internal environmental governance. This divergence indicates that the influence of celebrity leadership is shaped by complex moderating factors, rather than a simple linear relationship, highlighting the need for context-specific and contingency-based analyses in future research.
4.2 Analysis of Chinese-language research hotspots
4.2.1 Corporate greenwashing motivations and economic consequences under financing constraints
The financing constraint theory provides a crucial analytical framework for understanding the motivations behind corporate greenwashing. Existing studies generally recognize financing pressure as one of the primary drivers of strategic environmental disclosure. The rationale is that, while green finance policies facilitate access to credit and lower financing costs for firms with strong ESG performance, authentic green transformation often requires substantial capital investment—posing challenges for firms already facing liquidity constraints. Faced with a trade-off between compliance benefits and transition costs, some firms may exaggerate or fabricate ESG information to secure external funding, thereby incentivizing greenwashing (Xi et al., 2024).
Additionally, regional isomorphism tends to reinforce herding behaviors among firms (Huang et al., 2020), while managerial opportunism further increases the likelihood of strategic disclosure (Luo and Zhou, 2024). These findings suggest that financing constraints facilitate corporate greenwashing, a relationship amplified by information asymmetry, institutional pressure, and agency problems.
From an economic perspective, greenwashing exhibits a clear short-term benefit but long-term cost pattern. In the short term, successful greenwashing enables firms to project a positive environmental image, obtain valuation premiums, attract financing, and alleviate liquidity pressures (Luo and Zhou, 2024). However, such gains are typically unsustainable. Once exposed, firms face reputational damage, loss of investor confidence, and declines in market value. Even when undetected, persistent greenwashing erodes corporate culture, undermines internal governance, and weakens long-term competitiveness (Sun and Wu, 2019).
Yao and Wang (2025) demonstrate that ESG greenwashing significantly harms firms’ financial performance through two primary channels: exacerbating information asymmetry and reducing profitability. These adverse effects are particularly pronounced in labor-intensive, high-pollution, and high-tech industries, indicating that industry heterogeneity influences firms’ exposure to and ability to manage greenwashing risks.
Beyond the firm level, greenwashing also generates negative societal externalities. Wu et al. (2024) find that greenwashing exacerbates firms’ financing constraints and leads to employment contraction, reducing the labor income share within firms. This outcome contradicts ESG’s core goal of promoting social equity, suggesting that greenwashing is not just an issue of corporate disclosure quality or governance efficiency, but one that distorts income distribution and undermines sustainability of economic development.
Overall, financing constraints play a pivotal role in shaping greenwashing behavior. While greenwashing may yield short-term reputational and financial gains, it ultimately erodes corporate sustainability, damages market credibility, and undermines the effectiveness of green finance systems—posing systemic risks to both firms and the broader economy.
4.2.2 Institutional development of ESG disclosure and anti-greenwashing governance
As part of China’s “Dual-Carbon” strategy, establishing a coherent and effective institutional framework for ESG disclosure and greenwashing governance has become a central theme in both Chinese scholarship and practice. The core challenge lies in translating macro-level sustainability principles into actionable and verifiable mechanisms that align with China’s institutional context, effectively curbing corporate greenwashing. In response, an emerging body of literature has outlined a comprehensive research agenda spanning information generation, assurance, and enforcement. Within this framework, debates around disclosure modes and framework design have taken center stage, providing the foundation for institutional development.
4.2.2.1 Disclosure modes: balancing mandatory and voluntary systems
Research on disclosure modes primarily focuses on balancing mandatory and voluntary disclosure. Firm-initiated ESG reports often suffer from low standardization, inconsistent metrics, and questionable reliability, which impede verification and cross-firm comparability for investors and regulators. This information asymmetry lowers the expected cost of greenwashing and incentivizes opportunistic misreporting, leading to widespread calls for mandatory disclosure to improve transparency and accountability (Peng, 2023).
However, implementation remains contentious. Xu (2025) cautions that mandatory disclosure could impose excessive compliance burdens—particularly on firms in less-developed regions—if the UN principle of “common but differentiated responsibilities” is not considered, thereby undermining policy legitimacy. Li and An (2025) further emphasize the dynamic and pluralistic nature of ESG indicators, warning that rigid standards could hinder adaptive learning and innovation. Drawing on Teubner’s theory of Reflexive Law, they propose that legal frameworks should foster self-reflection and self-regulation through procedural norms, rather than prescribing rigid behavioral mandates.
4.2.2.2 Framework design: toward a phased and adaptive approach
In terms of framework design, Chinese scholars generally advocate for a gradual and pragmatic pathway. Li and Xiao (2024) suggest unifying mandatory disclosure standards, incentivizing high-quality voluntary disclosure, and avoiding the mechanical transplantation of foreign rules that may create institutional frictions. Building on China’s experience with environmental regulation and information disclosure, Wang et al. (2022) propose a phased implementation strategy: initially strengthening mandatory disclosure of environmental (E) information, then expanding to encompass a full ESG scope covering social (S) and governance (G) dimensions, and ultimately integrating financial and non-financial reporting into a unified framework.
This incremental approach reflects the internal logic of institutional evolution, balancing ambitious reform goals with adaptive capacity. By aligning regulatory progression with firms’ compliance readiness, it mitigates the cost pressures and adjustment challenges that would arise from immediate, full-scale implementation.
4.2.3 Prevention and management of greenwashing risks in the green finance system
Effectively preventing and managing greenwashing risks is increasingly recognized as a central challenge to the sustainable development of the green finance system. There is a growing concern among scholars that greenwashing may pose broader risks, evolving from isolated corporate misconduct into a potential systemic concern that could undermine market information reliability. Chinese research has evolved from early, single-perspective analyses of firm motivations to a multi-level, system-based governance framework aimed at achieving ex-ante prevention and process-oriented management through the coordinated interaction of policy mechanisms, technological innovation, and legal institutions.
4.2.3.1 Policy dimension: aligning incentives with substantive performance
At the policy level, imperfections in green finance mechanisms can themselves induce greenwashing (Su and Liu, 2023). The core issue lies in the arbitrage space between policy incentives and substantive environmental outcomes, as firms may strategically disclose ESG information to secure preferential financing. To address this, scholars emphasize the importance of fiscal–financial coordination mechanisms.
For example, green credit interest-subsidy policies operate through a dual mechanism of “promotion and constraint.” On one hand, fiscal subsidies directly reduce financing costs for legitimate green projects, easing firms’ financing constraints and diminishing their incentive to greenwash. On the other hand, qualification reviews for subsidy eligibility act as a hard constraint, compelling banks to strengthen pre-loan screening and post-loan supervision, thus improving the detection and prevention of greenwashing. These coordination mechanisms enhance resource allocation efficiency; however, scholars caution against over-reliance on subsidies and excessive implementation costs, advocating for a dynamic adjustment mechanism to balance incentive strength with fiscal sustainability (Hong et al., 2023; Li and Wang, 2025).
Information asymmetry and high verification costs remain fertile ground for greenwashing, as traditional risk-control approaches often fail to provide effective supervision. In this context, financial technology (FinTech) has demonstrated transformative potential. Yan et al. (2025) show that blockchain technology can establish a distributed and tamper-proof traceability system for green projects, ensuring data authenticity across certification, financing, and performance evaluation processes. Additionally, natural language processing (NLP) and big data analytics enable comparisons between firms’ stated environmental commitments and actual performance, facilitating the intelligent identification of inconsistencies that signal potential greenwashing. Together, these technologies are driving a paradigm shift in green finance risk management—from ex post static supervision to real-time dynamic monitoring.
4.2.3.2 Legal dimension: strengthening the rule of law and institutional coherence
At the legal level, a weak regulatory foundation remains a root cause of recurring greenwashing risks. Current issues include non-unified standards, lax disclosure requirements, and low penalties for violations. Wang (2024) argue that effective greenwashing governance requires strengthening the rule of law in both external regulatory frameworks and internal institutional design. Formally, this entails promoting unified high-level legislation that consolidates fragmented rules to enhance legal authority and enforceability. Substantively, it involves aligning Chinese green finance standards with international norms and establishing a mandatory environmental disclosure system.
While such a framework can stabilize market expectations and reinforce compliance, scholars also caution against potential tensions between regulatory rigidity and market innovation. The applicability of uniform standards across regions and industries poses additional implementation challenges. Achieving an appropriate balance between principled regulation and adaptive flexibility is therefore crucial for the effective, sustainable governance of green finance.
5 A review of academic countermeasures to ESG greenwashing
Academic approaches to countering ESG greenwashing primarily focus on three areas: regulation and policy intervention, corporate governance and incentive mechanisms, and technological innovation and information transparency.
In the area of regulation and policy intervention, Yin et al. (2024) examined China’s new Environmental Protection Law (EPL) and found that the law effectively curbed corporate ESG greenwashing through institutional deterrence, cost reduction, and alleviation of financing constraints. They recommend strengthening targeted enforcement (e.g., toward private enterprises), providing green credit and tax incentives, and supporting environmental technology research and development at the macro level. At the micro level, companies should integrate green concepts into their corporate culture, link executive performance to ESG metrics, and increase investment in green technologies. Cheng and Yan (2025) explored the impact of Environmental Management System Certification (EMSC) on ESG greenwashing, discovering that EMSC mitigated greenwashing behaviors by suppressing earnings management, enhancing stakeholder oversight, and reducing inefficient investments. They advocate for a globally unified ESG misreporting accountability system, using EMSC as a mandatory threshold for green tax incentives and government procurement, and promoting mutual recognition between ISO 14001 and ISSB standards to enhance the credibility of certification data. At the corporate level, they suggest establishing environmental committees with veto power.
In the context of corporate governance and incentive mechanisms, Wang et al. (2025)‘s empirical research highlighted the significant role of the Social Credit System (SCS) in curbing corporate ESG greenwashing, mainly by alleviating financing constraints and reducing agency costs. They recommend accelerating the promotion of the credit system, implementing a tiered punishment mechanism, and strengthening social supervision. Li et al. (2025) conducted the first systematic analysis of the impact of retail investor attention on ESG greenwashing and found that such attention exacerbated greenwashing behaviors. They encourage analysts and institutional investors to assess ESG authenticity more thoroughly and recommend enhancing investor education to improve the discernment capabilities of retail investors, reducing the risk of being misled.
In terms of technological innovation and information transparency, Xu et al. (2025) proposed a framework driven by dual-layer large language models (LLM) to detect greenwashing behaviors, addressing the limitations of traditional methods such as manual audits and word frequency statistics. Montero-Navarro et al. (2021) demonstrated the effectiveness of fine-tuning LLMs for ESG text analysis, offering scalable solutions for greenwashing detection. Their approach enhances transparency and integrity in the ESG investment ecosystem by providing quantifiable scoring and ranking.
6 Conclusion, limitations, and future directions
This study provides a systematic review and visual analysis of research on ESG greenwashing from 2017 to 2025, uncovering its development trajectory and key characteristics, while summarizing the countermeasures proposed by scholars. As the concept of sustainable development continues to evolve, ESG greenwashing has become a central issue in both academia and industry. By analyzing research progress in both Chinese and international contexts, it is evident that international research began earlier, initially focusing on green marketing strategies, corporate management practices, and legitimacy issues. Over time, the focus shifted toward corporate sustainability and ESG disclosure, with more recent studies expanding into areas like AI governance and sustainable finance. In contrast, Chinese-language research tends to emphasize practical issues, such as the motivations behind corporate greenwashing, the development of ESG disclosure systems, and green finance risk management, reflecting a strong policy orientation and practical application.
However, this study has several limitations. Due to the limited number of Chinese-language studies, no specific restrictions were applied to sources like CSSCI or Peking University Core Journals, which may affect the representativeness of the literature. Additionally, the literature data for this study were drawn solely from the CNKI (China National Knowledge Infrastructure) and Web of Science databases, excluding other potential sources of relevant literature, which may impact the comprehensiveness of the literature search. Furthermore, CiteSpace has limited capacity for exploring deeper underlying mechanisms. Another limitation is that excluding studies prior to 2017 may disrupt the historical development of greenwashing research and narrow the understanding of long-term evolutionary patterns. Moreover, the inclusion of publications from 2025, with data collected up to September 15, means that the annual count for this year is incomplete. While this allows for the inclusion of the most recent research trends, it may introduce a minor structural bias when comparing publication volumes against full-year data from previous periods.
Looking forward, future research on ESG greenwashing can explore several areas: First, future research could focus on designing AI systems with inherent anti-manipulation capabilities to mitigate the risks of “machine washing.” A key approach in this regard is the use of adversarial training, which can strengthen the model’s robustness against common manipulations, such as greenwashing rhetoric. Additionally, incorporating explainable AI techniques would be crucial, enabling the model not only to output the probability of greenwashing but also to identify key phrases and provide the underlying logic supporting its decision. This approach would make manipulation more challenging and enhance the transparency and accountability of AI systems, ensuring they are more resilient to complex linguistic manipulations. Second, how firms perceive and interpret external institutional pressures, such as policies like China’s “dual carbon” targets, is a crucial area of research. Firms may view such pressures as an opportunity for transformation or as a compliance threat. Future research could explore the differences in these subjective interpretations and examine how they mediate the relationship between institutional pressures and firms’ ultimate choices, whether to engage in greenwashing or to implement substantive reforms. Third, there is still considerable debate in the academic literature regarding the influence of executive characteristics on greenwashing behavior, particularly concerning whether female executives can mitigate such behavior. Future research could conduct empirical analyses in different contexts to further explore how this relationship varies and to uncover how various factors influence executive decision-making in diverse environments. Finally, coordination and conflict of policy instruments. Different policy instruments, such as green credit, green bonds, environmental taxes, and carbon market could potentially weaken the governance effect of green credit. Future research could focus on designing policy mixes that are incentive-compatible, directing resources toward genuinely green activities.
Data availability statement
The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.
Author contributions
GH: Methodology, Validation, Data curation, Software, Visualization, Formal analysis, Resources, Funding acquisition, Writing – original draft. ZX: Software, Methodology, Writing – original draft, Data curation, Resources, Visualization. WC: Supervision, Validation, Resources, Project administration, Writing – review & editing.
Funding
The author(s) declared that financial support was received for this work and/or its publication. This research was supported by the Department of Education of Guangdong Province under the Guangdong College Students’ Innovation and Entrepreneurship Training Program (no: S202510590056).
Acknowledgments
The authors would like to acknowledge the support from Guangdong College Students’ Innovation and Entrepreneurship Training Program (no: S202510590056).
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that Generative AI was not used in the creation of this manuscript.
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Keywords: bibliometric analysis, CiteSpace, ESG, ESG disclosure, greenwashing, sustainability
Citation: Hu G, Xu Z and Chen W (2026) Comparative mapping of ESG greenwashing research between China and the global context: a CiteSpace-based bibliometric analysis. Front. Sustain. 6:1738383. doi: 10.3389/frsus.2025.1738383
Edited by:
Omaima Hassan, Robert Gordon University, United KingdomReviewed by:
Diana Elena Vasiu, Lucian Blaga University of Sibiu, RomaniaCopyright © 2026 Hu, Xu and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Weimin Chen, d21pbmNAMTI2LmNvbQ==