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Purpose

This study aims to provide a comprehensive overview of the temporal evolution of greenwashing practices through bibliometric analysis.

Design/methodology/approach

Companies involved in environmental, social and governance (ESG) fraud exploit the information gap between themselves and investors, consumers or regulators, capitalizing on the absence of robust verification mechanisms for sustainability data. This research employs a bibliometric analysis of fraud in sustainability reporting. We employed VOSviewer software, which identifies connections and trends within a large volume of information and provides a visual map of the most significant elements in the field. The article specifically analyzes academic literature related to greenwashing published between 1976 and 2025, covering 3,004 publications on the Web of Science.

Findings

The findings underscore the escalating involvement of corporations in practices commonly referred to as greenwashing. This phenomenon can be attributed to the increasing public pressure from various stakeholders, prompting organizations to respond to these expectations predominantly through misleading communication rather than implementing substantive environmental initiatives.

Research limitations/implications

One significant limitation of this research is its predominant reliance on bibliometric and network analysis through the use of VOSviewer, which necessitates the employment of standardized scientific databases.

Practical implications

The research makes governments and companies aware of the need to implement genuine sustainability policies, a rising demand for transparency in ESG reporting and changing consumer perceptions following the pandemic.

Social implications

This analysis aims to elucidate the evolution of greenwashing in scholarly research, thereby enriching our understanding of its trajectory and implications within the wider context of environmental discourse.

Originality/value

This research is valuable for researchers and academics, as it provides insights into the evolution of the greenwashing concept, current trends and areas that have not been extensively studied. Investors and financial analysts may also find the findings helpful for accurately assessing companies’ sustainable performance when making capital allocation decisions. Additionally, regulators and public authorities are an important audience, as they are responsible for developing and enforcing policies aimed at preventing misleading sustainability disclosures.

During the COVID-19 pandemic, companies around the world faced enormous pressure from the public, investors and authorities to demonstrate not only economic resilience but also social and environmental responsibility.

Several factors contributed to the increased incidence of greenwashing during the pandemic. One of these was informational opacity: the pandemic disrupted normal verification and audit mechanisms (such as on-site visits and independent inspections), making it easier for companies to claim environmental or social performance without being rigorously checked. ESG marketing as a survival strategy is another factor that led to increased greenwashing (Yildirim, 2023). For many financially affected companies, attracting ESG investments became a lifeline strategy. As a result, they felt compelled to embellish their “green” profile to access funding, even if the reality did not support those claims.

In recent years, the environmental, social and governance (ESG) criteria have become essential benchmarks for assessing corporate responsibility and sustainable investments. However, alongside their rise, major controversies have emerged. The lack of clear and uniform standards in the application and reporting of ESG criteria has created opportunities for companies to enhance their public image without implementing real changes. This phenomenon, known as greenwashing, involves promoting superficial environmental or social initiatives to attract sustainability-minded investors and consumers, without backing these claims with concrete practices. Thus, instead of encouraging genuine and responsible corporate behavior, the controversies surrounding ESG may contribute to the perpetuation of misleading communication strategies and the erosion of trust in companies’ sustainability commitments.

Two examples in this regard are Microsoft and Amazon, which during the pandemic launched highly ambitious initiatives such as “carbon neutral” or “climate pledge” commitments. For instance, in 2020, Amazon announced “The Climate Pledge,” promising to become carbon-neutral by 2040. The company launched extensive advertising campaigns about investments in renewable energy, electric vehicles and reforestation projects. However, at the same time, Amazon continued to expand its rapid logistics network (one-day and two-day deliveries), a highly energy-intensive model. The carbon impact of its massive server infrastructure (AWS – Amazon Web Services), which consumes enormous amounts of energy, was only partially reported. Many of its “green” promises were vague or relied heavily on purchasing carbon credits rather than effectively reducing its own emissions.

Similarly, in 2020, Microsoft pledged to become “carbon negative” by 2030. Nevertheless, it continued to sign large-scale cloud computing contracts with polluting industries (such as oil and gas), while simultaneously promoting an image as an environmental leader. There were accusations that its sustainability reports were crafted to sound impressive but deliberately avoided addressing indirect emissions (Scope 3 emissions), which make up the largest share of its carbon footprint.

This paper seeks to advance the contemporary discourse surrounding greenwashing practices by offering a comprehensive review of both historical and current developments in academic literature. Through extensive bibliometric analysis, this study encompasses 3,004 publications indexed in the Web of Science from 1976 to 2025, focusing specifically on the temporal dynamics associated with greenwashing practices. This analysis aims to elucidate the evolution of greenwashing in scholarly research, thereby enriching our understanding of its trajectory and implications within the wider context of environmental discourse.

The study highlights the growing interest in sustainability, the adaptation of non-financial frauds (the lack of clear ESG standards has allowed companies to exaggerate or falsify their environmental performance), the increasing pressure of regulations (in the EU and other regions, non-financial reporting standards are becoming stricter – CSRD, Green Taxonomy) and the reputational and investment impact.

In the absence of unified standards and effective verification mechanisms, numerous economic entities have exploited ambiguities in the reporting framework to polish their public image. Thus, the critical analysis of these practices becomes essential not only for identifying and combating emerging forms of non-financial fraud but also for supporting the development of stricter regulatory policies, adapted audit tools and an ethical framework that ensures transparency and integrity in the communication of environmental performance by organizations.

Although existing literature defines greenwashing as a form of selective disclosure intended to mislead stakeholders about environmental performance (Delmas and Burbano, 2011), most studies focus on traditional communication and marketing practices. Through this study, we aim to capture the post-pandemic context in sustainability fraud, which is also the originality of the paper. Sustainability fraud has become more sophisticated, involving the entire reporting process, digital technologies (including AI, falsified blockchain or algorithmic manipulation) and increasingly affecting technological industries. However, current literature has not sufficiently investigated the areas that can facilitate or conceal greenwashing and ESG fraud in innovative industries, leaving a knowledge gap regarding new forms of manipulation and effective detection methods.

This article is structured based on the research objectives and its contributions to existing literature. Section 2 offers a brief review of previous studies to identify the gaps this paper seeks to address. Section 3 details the research methodology employed. Section 4 presents the results, while Section 5 includes the discussion. Finally, Section 6 outlines the conclusions, discusses the paper’s limitations and suggests directions for future research.

ESG frauds are typically intentional and focused on achieving short-term profits. However, they result in significant financial and reputational damage in the long run. This behavior can be understood through the economic theory of utility maximization, which suggests that corporate decision-makers often prioritize immediate advantages – such as access to ESG capital, increases in stock prices and enhancements to their public image – over the perceived long-term risks involved.

Greenwashing enhances a company’s reputation, allows it to comply with regulatory standards and lowers financial expenses by attracting the interest of financial institutions. However, these “benefits” available to unethical companies may contribute to the proliferation of greenwashing and a decline in genuine sustainability efforts (Arouri et al., 2021).

Some researchers view greenwashing as a form of fraud related to information disclosure and apply the fraud triangle model to study it (He et al., 2021; Kurpierz and Smith, 2020). This model identifies three fundamental components that contribute to fraud: pressure, opportunity and rationalization. Pressure, often referred to as motivation, typically stems from the need to achieve financial goals or meet stakeholder expectations, which can be intensified by intense market competition (Zhu et al., 2023) and financial pressures (Lederman, 2021). Opportunity pertains to situations that enable fraudulent behavior, such as weak internal controls and information asymmetry. Rationalization involves the ethical attitudes or values that justify unethical actions, like a CEO’s overconfidence (Lederman, 2021). Among these components, pressure and opportunity are considered the primary drivers of fraud (Kurpierz and Smith, 2020).

Another way of addressing fraud relates to enterprise crisis management, which can be used to handle various crises through planning and decision-making, dynamic adjustment, resolution and staff training. The primary goal is to eliminate or reduce the threats and losses caused by these crises. In China, corporate crises typically fall into three main categories: online criticism from the public (Wang and Laufer, 2020; Wang et al., 2021), negative media coverage and regulatory penalties imposed by official or authorized organizations (Dhanesh and Sriramesh, 2018). One example of a regulatory sanction is the issuance of comment letters on financial disclosures by oversight bodies, which can reduce public trust in companies and heighten their reliance on external financing (Zhu et al., 2023). Therefore, firms have incentives to proactively manage crises to mitigate the detrimental effects of receiving these comment letters. Companies typically employ four main strategies to address crises. First, in response to negative events, some organizations choose to issue statements, communicate proactively, change directors, increase environmental donations and implement other positive measures to minimize the crises’ impact. Second, some firms adopt a silent or denial strategy, which can also help them navigate through the crisis. Third, research has shown that companies sometimes utilize “barnacle” strategies that involve controlling media narratives to lessen public criticism and manage crises. Finally, some firms release unrelated information in order to distract the public’s attention and alleviate social concerns following a crisis (Liao et al., 2023).

ESG controversies represent another way of engaging in fraud. ESG controversies translate into financial risks (Weinmayer et al., 2023; Kolbel et al., 2017). These controversies often clash with investor expectations and create increased uncertainty about a company’s value. Weinmayer et al. (2023) also find that companies facing ESG controversies tend to enhance their ESG disclosures in their annual reports. Their analysis indicates that companies with more comprehensive ESG disclosures are better shielded from negative market reactions following such controversies. Further research suggests that robust ESG disclosure helps build “ethical” capital, which can serve as a form of insurance for firms, protecting them against adverse consequences during crises.

Schiemann and Tietmeyer (2022) demonstrate that companies experiencing higher ESG controversies tend to face greater uncertainty. However, they also find that this relationship is weakened for companies that provide strong ESG disclosure. Their further analyses indicate that this connection is particularly pronounced for social controversies and social disclosure. Additionally, they highlight that external pressure resulting from controversies in the three different ESG pillars leads to increased disclosure across all respective pillars.

Kirk and Vincent (2014) illustrate that companies may choose to disclose ESG information selectively to certain investors. As a result, companies facing financial constraints are more likely to create a misleading impression of their actual environmental performance. Specifically, companies with high leverage are financially constrained, which means that their profit-maximizing activities are more expensive (Zhang and Du, 2020). Pollution control can create a substitution effect for profit-directed investments, such as investments in fixed assets and intangible assets (Zhang and Vinge, 2021). Consequently, firms with high leverage tend to be particularly sensitive to financial constraints and costs, making them more prone to engage in greenwashing. Companies with limited resources may use corporate social responsibility (CSR) as a “greenwashing” tool, aiming to enhance their environmental and social image without making significant investments in genuine improvements in their CSR performance.

Kim et al. (2012) synthesize theoretical propositions from the literature and identify two types of CSR firms. The first type is dedicated to ethical environmental and social practices, investing significant resources to implement CSR governance for the greater social good. These firms are likely to achieve positive results in CSR initiatives, leading to improved business performance and enhanced social legitimacy. The second type of CSR firm, referred to as “greenwashing” firms, engages in opportunistic behavior aimed at improving their corporate image without genuinely committing to responsible ecological and social governance. As a result, these greenwashing firms may create a legitimacy gap due to their poor performance in CSR, which can hinder their potential for both short-term and long-term profits.

Yuan et al. (2024) identify three strategies commonly associated with greenwashing. The first strategy is “exaggeration,” where firms tend to overstate their actual environmental efforts. This practice, often described as “more talk than action,” has been highlighted in previous studies (Yu et al., 2020; Zhang, 2023) and is referred to as greenwashing E. The second strategy, called “attention diversion” (greenwashing D), involves firms using positive environmental initiatives to divert attention from unethical behaviors. Many studies that focus on ESG aspects categorize these initiatives as strengths while downplaying concerns, since they can have different economic consequences (Nofsinger et al., 2019). This behavior is reminiscent of the Chinese saying: “Pretending to advance on one path while secretly walking on another,” which has been validated in some research on ESG disclosure (Zhang, 2023). The third strategy is “window-dressing” (greenwashing W). This refers to superficial or cosmetic changes made to financial situations, reports or other disclosures to present the company in a more favorable light. Khan et al. (2016) note that the significance of environmental sustainability issues can differ by firm and industry. For instance, electricity supply companies may prioritize managing air pollution, while biological research institutions are more focused on animal habitat protection. In this study, we define “window-dressing” as presenting immaterial environmental achievements to enhance a company’s ecological image without addressing the major environmental damages they may be causing.

Financial institutions have begun using ESG information disclosed by companies to evaluate investment risks and opportunities (Yu et al., 2020). When firms voluntarily disclose CSR and ESG information, it can encourage them to make more informed investment decisions that promote sustainable growth. This includes accessing green credits and reducing financial costs (Dhaliwal et al., 2011; Ghoul et al., 2018; Wen et al., 2021). However, incorporating ESG information into the credit selection process can also lead to firms providing misleading ESG disclosures. The greater the discrepancy between these misleading disclosures and the firms’ actual ESG performance – a phenomenon referred to as “greenwashing” – the lower the firm’s sustainable efficiency (Van Halderen et al., 2016; Yu et al., 2020).

There is evidence that taking actions to improve sustainable performance, such as engaging in CSR activities, can enhance firms’ financial performance (Kim et al., 2018). For instance, green credit could bolster corporate social responsibility efforts and subsequently improve overall firm performance (He et al., 2019). Moreover, measuring sustainable performance through ESG indicators is crucial for effectively managing a company’s risk (Marquis et al., 2016; Yu et al., 2018).

The implementation of green financial regulations aims to promote sustainable growth, significantly affecting highly polluting firms. These firms face external credit pressures and increased financial costs (Hu et al., 2021). Additionally, they are heavily influenced by green finance regulations, which may lead them to present selective signals of sustainable performance. This can mislead decision-makers and financial institutions as they attempt to meet policy requirements and alleviate financial challenges. Moreover, since firms generally seek to maximize profits, the financial difficulties faced by highly polluting firms can create strong incentives for them to maintain profitability (Zhang and Du, 2020).

In the post-pandemic context, many companies are facing heightened public pressure to adopt sustainable practices. However, not all of them are genuinely committed to sustainability. Greenwashing – the act of misleadingly promoting environmental responsibility – has evolved in response to the new concerns of consumers and investors. This paper aims to achieve two primary objectives. First, we will identify through a literature review the economic sectors where greenwashing practices are most prevalent, such as fashion, energy, transportation and technology. It will also analyze how the global health crisis has impacted the communication and marketing strategies of these companies. Second, the paper will explore how ESG requirements have prompted either meaningful improvements or the refinement of greenwashing tactics.

This study aims to explore the concept of greenwashing and to analyze its relevance in the literature through bibliometric methods. To achieve this, we extracted data from the Web of Science Core Collection, one of the most prominent scientific publication platforms globally, which has been a key research tool for decades. We chose this database because it contains high-quality publications noted for their accuracy and relevance in scientific research. Web of Science constitutes a robust tool for identifying relevant literature and monitoring emerging trends in the investigated field, offering a considerable advantage over more permissive or lower-quality databases. Additionally, the platform covers a comprehensive research period, with studies on the concept dating back to 1976. We accessed the Web of Science database for information extraction on March 26, 2025.

A search conducted in the Web of Science used the terms “green” and “*washing,” yielding a total of 3,116 articles. We refined this number based on several criteria. First, we selected only articles, proceedings papers, review articles and early access documents, which narrowed the total down to 3,092 articles, as illustrated in Figure 1. The second refinement was based on language, focusing only on documents published in English. Our final sample consists of 3,004 documents published from 1976 to March 2025, as shown in Figure 2.

Figure 1
A vertical bar graph is shown with the number of document types.The vertical axis ranges from 0 to 2600 in increments of 200 units. The horizontal axis is labeled “Article,” “Book Chapters,” “Early Access,” “Proceeding Paper,” and “Review Article.” The data for the bars are as follows: Article: 2751. Book Chapters: 40. Early Access 113. Proceeding Paper: 193. Review Article: 153. Note: All numerical data values are approximated.

Document types. Source: Web of science

Figure 1
A vertical bar graph is shown with the number of document types.The vertical axis ranges from 0 to 2600 in increments of 200 units. The horizontal axis is labeled “Article,” “Book Chapters,” “Early Access,” “Proceeding Paper,” and “Review Article.” The data for the bars are as follows: Article: 2751. Book Chapters: 40. Early Access 113. Proceeding Paper: 193. Review Article: 153. Note: All numerical data values are approximated.

Document types. Source: Web of science

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Figure 2
A Flowchart with four stages of article filtration, ending with a bibliometric review of 3,004 articles.The flowchart given has a staircase diagram with four boxes, beginning at the top left and ending at the lower right. The flow begins with a box labeled “Stage 1: Database search.” The text inside reads: “Database: Web of Science, “Keywords: “green” and “asterisk washing,” Period: 1976 to 2025, Included: 3,116 articles.” From this box, a double-headed arrow rises and points to a box at the bottom right labeled “Stage 2: Scholarly filtration.” The text inside reads: “Article type: articles, proceedings papers, review articles, and early access documents. Included: 3,092 articles.” On the right side of this box, a label reads as follows: “24 articles excluded.” From “Stage 2,” a double-headed arrow leads to the next box labeled “Stage 3: Language filtration.” The text inside reads: “Language: English, Included: 3,004 articles.” On the right side of this box, a label reads as follows: “88 articles excluded.” From “Stage 3,” a double-headed arrow arises and points to the final box labeled “Bibliometric review.” The text inside reads: “Included: 3,004 articles.”

Database refinement. Source: Authors’ processing

Figure 2
A Flowchart with four stages of article filtration, ending with a bibliometric review of 3,004 articles.The flowchart given has a staircase diagram with four boxes, beginning at the top left and ending at the lower right. The flow begins with a box labeled “Stage 1: Database search.” The text inside reads: “Database: Web of Science, “Keywords: “green” and “asterisk washing,” Period: 1976 to 2025, Included: 3,116 articles.” From this box, a double-headed arrow rises and points to a box at the bottom right labeled “Stage 2: Scholarly filtration.” The text inside reads: “Article type: articles, proceedings papers, review articles, and early access documents. Included: 3,092 articles.” On the right side of this box, a label reads as follows: “24 articles excluded.” From “Stage 2,” a double-headed arrow leads to the next box labeled “Stage 3: Language filtration.” The text inside reads: “Language: English, Included: 3,004 articles.” On the right side of this box, a label reads as follows: “88 articles excluded.” From “Stage 3,” a double-headed arrow arises and points to the final box labeled “Bibliometric review.” The text inside reads: “Included: 3,004 articles.”

Database refinement. Source: Authors’ processing

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After obtaining the sample mentioned above, we conducted a bibliometric analysis using the scientific mapping methodology. For this, we utilized VOSviewer software (Centre for Science and Technology Studies, Leiden University, Netherlands, 2020), which is specifically designed for constructing and visualizing bibliometric networks.

The pandemic has heightened global awareness of ESG issues, leading to an increase in publications and articles focused on topics related to greenwashing, as illustrated in Figure 3. In their efforts to maintain a positive reputation, some companies engage in greenwashing, which raises ethical questions and discussions in various publications. Notably, interest in studying greenwashing has shown a significant upward trend during the reviewed period. For example, the number of papers on this topic in the Web of Science database rose from 239 in 2021 to 309 in 2022. In 2023, the number increased to 346 and then further to 474 papers in 2024.

Figure 3
A vertical bar graph shows the evolution of publications on greenwashing from 2016 to 2025.The vertical axis ranges from 0 to 450 in increments of 50 units. The horizontal axis is labeled with years from 2016 to 2025 in increments of 1 unit. The data for the bars are as follows: 2016: 99. 2017: 125. 2018: 165. 2019: 170. 2020: 214. 2021: 240. 2021: 314. 2022: 310. 2023: 345. 2024: 475. 2025: 115. Note: All numerical data values are approximated.

Evolution of publications on greenwashing. Source: Web of science

Figure 3
A vertical bar graph shows the evolution of publications on greenwashing from 2016 to 2025.The vertical axis ranges from 0 to 450 in increments of 50 units. The horizontal axis is labeled with years from 2016 to 2025 in increments of 1 unit. The data for the bars are as follows: 2016: 99. 2017: 125. 2018: 165. 2019: 170. 2020: 214. 2021: 240. 2021: 314. 2022: 310. 2023: 345. 2024: 475. 2025: 115. Note: All numerical data values are approximated.

Evolution of publications on greenwashing. Source: Web of science

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Figure 4 illustrates the evolution of citations for these articles over the studied period. Notably, by 2024, the number of citations exceeded 14,000. The year 2025 could not be included in this analysis since it was conducted in March 2025. The significant rise in citations for publications related to greenwashing, particularly in the last three years, highlights the growing popularity and impact of this topic within academic circles.

Figure 4
A vertical bar graph shows the evolution of citations on greenwashing from 1976 to 2025.The horizontal axis is labeled with years from 1976 to 2025 in increments of 1 unit. The graph has two vertical axes. The vertical axis on the left is labeled “Publications” and ranges from 0 to 450 in increments of 50 units. The vertical axis on the right is labeled “Citations” and ranges from 0 to 14,000 in increments of 2,000 units. The graph shows vertical bars and a curve. A legend at the bottom states that the bar represents “Publications” and the curve represents “Citations.” The curve begins at (1975, 150) and remains flat until 2000. It then gradually rises and passes through the points (2017, 2,058) and (2023, 10,423). It peaks at (2024, 14,320) and ends at (2025, 3,788). The data for the bars are as follows: 1976: 15. 1977: 5. 1978: 8. 1979: 12. 1980: 15. 1981: 17. 1982: 12. 1983: 5. 1984: 5. 1985: 5. 1986: 5. 1987: 5. 1988: 5. 1989: 5. 1990: 5. 1991: 18. 1992: 5. 1993: 5. 1994: 17. 1995: 18. 1996: 15. 1997: 15. 1998: 20. 1999: 21.5. 2000: 17. 2001: 24. 2002: 30. 2003: 26. 2004: 34.5. 2005: 35. 2006: 35. 2007: 44. 2008: 30. 2009: 45. 2010: 52. 2011: 71. 2012: 71. 2013: 71. 2014: 81. 2015: 86. 2016: 99. 2017: 127. 2018: 165. 2019: 170. 2020: 212. 2021: 242. 2022: 311. 2023: 347. 2024: 500. 2025: 118. Note: All numerical data values are approximated.

Evolution of citations on greenwashing. Source: Web of science

Figure 4
A vertical bar graph shows the evolution of citations on greenwashing from 1976 to 2025.The horizontal axis is labeled with years from 1976 to 2025 in increments of 1 unit. The graph has two vertical axes. The vertical axis on the left is labeled “Publications” and ranges from 0 to 450 in increments of 50 units. The vertical axis on the right is labeled “Citations” and ranges from 0 to 14,000 in increments of 2,000 units. The graph shows vertical bars and a curve. A legend at the bottom states that the bar represents “Publications” and the curve represents “Citations.” The curve begins at (1975, 150) and remains flat until 2000. It then gradually rises and passes through the points (2017, 2,058) and (2023, 10,423). It peaks at (2024, 14,320) and ends at (2025, 3,788). The data for the bars are as follows: 1976: 15. 1977: 5. 1978: 8. 1979: 12. 1980: 15. 1981: 17. 1982: 12. 1983: 5. 1984: 5. 1985: 5. 1986: 5. 1987: 5. 1988: 5. 1989: 5. 1990: 5. 1991: 18. 1992: 5. 1993: 5. 1994: 17. 1995: 18. 1996: 15. 1997: 15. 1998: 20. 1999: 21.5. 2000: 17. 2001: 24. 2002: 30. 2003: 26. 2004: 34.5. 2005: 35. 2006: 35. 2007: 44. 2008: 30. 2009: 45. 2010: 52. 2011: 71. 2012: 71. 2013: 71. 2014: 81. 2015: 86. 2016: 99. 2017: 127. 2018: 165. 2019: 170. 2020: 212. 2021: 242. 2022: 311. 2023: 347. 2024: 500. 2025: 118. Note: All numerical data values are approximated.

Evolution of citations on greenwashing. Source: Web of science

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Among the articles selected for this analysis, the most cited one is highlighted in Figure 5, with a total of 1,169 citations. Additionally, we employed the Litmaps application to visualize the citation evolution of the article by Delmas and Burbano, as illustrated in Figure 6.

Figure 5
A figure shows a citation overview for the publication “The Drivers of Greenwashing”.The figure is divided into two main sections. On the left side, at the top left, the text “3,004 Publications” is displayed. On the top right, a drop-down menu titled “Citations: highest first” is visible. Next to the menu, a pagination control indicates that the current record is “1 of 61” entries. The main entry in the section at the bottom displays the title “The Drivers of Greenwashing,” with the word “Greenwashing” highlighted in yellow. Before the title, a small circular icon with a hyphen symbol is shown along with the number 1. Beneath the title, the text reads: “Delmas, M A and Burbano, V C,” followed by “Fall 2011” and the journal name “California Management Review.” Next to this, a small drop-down button appears, followed by the text “54 (1), pages 64 plus.” On the right side, a table is shown. The table is titled “Citations” at the top and contains 3 rows and 3 columns. Row 1 contains the column headers. The column headers are as follows: Column 1: This column shows the previous year and next year factors. This column shows the previous years selected. Column 2: “Average per year.” Column 3: “Total.” Column 1 is subdivided into 5 sub columns and titled as follows: Sub column 1: “2021,” Sub column 2: “2022,” Sub column 3: “2023,” Sub column 4: “2024,” and Sub column 5: “2025.” Row 2 presents “Total.” The row-wise data presented in the table is as follows: Row 2: Total; 2021: 7,413; 2022: 8,891; 2023: 10,375; 2024: 14,285; 2025: 3,661; Average per year: 1,436.2; Total: 70,374. Row 3: 2021: 138; 2022: 156; 2023: 179; 2024: 263; 2025: 68; Average per year: 77.93; Total: 1,169.

Most cited paper on greenwashing. Source: Web of science

Figure 5
A figure shows a citation overview for the publication “The Drivers of Greenwashing”.The figure is divided into two main sections. On the left side, at the top left, the text “3,004 Publications” is displayed. On the top right, a drop-down menu titled “Citations: highest first” is visible. Next to the menu, a pagination control indicates that the current record is “1 of 61” entries. The main entry in the section at the bottom displays the title “The Drivers of Greenwashing,” with the word “Greenwashing” highlighted in yellow. Before the title, a small circular icon with a hyphen symbol is shown along with the number 1. Beneath the title, the text reads: “Delmas, M A and Burbano, V C,” followed by “Fall 2011” and the journal name “California Management Review.” Next to this, a small drop-down button appears, followed by the text “54 (1), pages 64 plus.” On the right side, a table is shown. The table is titled “Citations” at the top and contains 3 rows and 3 columns. Row 1 contains the column headers. The column headers are as follows: Column 1: This column shows the previous year and next year factors. This column shows the previous years selected. Column 2: “Average per year.” Column 3: “Total.” Column 1 is subdivided into 5 sub columns and titled as follows: Sub column 1: “2021,” Sub column 2: “2022,” Sub column 3: “2023,” Sub column 4: “2024,” and Sub column 5: “2025.” Row 2 presents “Total.” The row-wise data presented in the table is as follows: Row 2: Total; 2021: 7,413; 2022: 8,891; 2023: 10,375; 2024: 14,285; 2025: 3,661; Average per year: 1,436.2; Total: 70,374. Row 3: 2021: 138; 2022: 156; 2023: 179; 2024: 263; 2025: 68; Average per year: 77.93; Total: 1,169.

Most cited paper on greenwashing. Source: Web of science

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Figure 6
A figure shows a litmap of a citation network starting from the most cited paper on greenwashing.The map has a right-pointing arrow at the bottom labeled “MORE RECENTLY PUBLISHED.” On the right side, an upward arrow labeled “MORE CITATIONS” is present. On the top right, a logo shows an icon of an acute angle formed by three data points accompanied by the text “Litmaps.” In the litmap, clusters of nodes are displayed, each represented by circles with labels and connected by thin lines indicating relationships, with labels adjacent to the nodes. All the circular nodes are shown with a blue outline, but on the top left, a black node is labeled “Delmas, 2011.” Adjacent to it, a large circular node is also labeled “Delmas, 2011.” From the black circular node labeled “Delmas, 2011,” the flow moves toward the bottom right. As the flow continues downward, the size of the circles also decreases. The labels of the circles in ascending order from top left to bottom right are as follows: “Lyon, 2015,” “Lyon, 2013,” “Bowen, 2014,” “Berrone, 2017,” “Hyatt, 2017,” “Yu, 2021,” “Kiriu, 2020,” “Becker-Ritterspach, 2019,” “Thimm, 2022,” “Dorfleitner, 2023,” “Hyatt, 2011,” “Guo, 2014,” “Shahudin, 2015,” “Tervonen, 2015,” “Risi, 2019,” “Diez-Busto, 2022,” and “Saravade, 2025.”

Citation network starting from the most cited paper on greenwashing. Source: Litmaps

Figure 6
A figure shows a litmap of a citation network starting from the most cited paper on greenwashing.The map has a right-pointing arrow at the bottom labeled “MORE RECENTLY PUBLISHED.” On the right side, an upward arrow labeled “MORE CITATIONS” is present. On the top right, a logo shows an icon of an acute angle formed by three data points accompanied by the text “Litmaps.” In the litmap, clusters of nodes are displayed, each represented by circles with labels and connected by thin lines indicating relationships, with labels adjacent to the nodes. All the circular nodes are shown with a blue outline, but on the top left, a black node is labeled “Delmas, 2011.” Adjacent to it, a large circular node is also labeled “Delmas, 2011.” From the black circular node labeled “Delmas, 2011,” the flow moves toward the bottom right. As the flow continues downward, the size of the circles also decreases. The labels of the circles in ascending order from top left to bottom right are as follows: “Lyon, 2015,” “Lyon, 2013,” “Bowen, 2014,” “Berrone, 2017,” “Hyatt, 2017,” “Yu, 2021,” “Kiriu, 2020,” “Becker-Ritterspach, 2019,” “Thimm, 2022,” “Dorfleitner, 2023,” “Hyatt, 2011,” “Guo, 2014,” “Shahudin, 2015,” “Tervonen, 2015,” “Risi, 2019,” “Diez-Busto, 2022,” and “Saravade, 2025.”

Citation network starting from the most cited paper on greenwashing. Source: Litmaps

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Figure 6 shows a citation map for a scientific article, which illustrates the relationships between various works. The horizontal axis (left to right) denotes the publication year, placing older articles on the left and newer ones on the right. The vertical axis (top to bottom) indicates the number of citations – articles positioned higher on the map have received more citations. The size of the circles reflects the citation counts, with the large, dark circle representing the most cited work (Delmas and Burbano, 2011). Lines connecting the circles indicate citation links; if one article cites another, a line will connect them. The blue outlines of the circles highlight works that are directly related to the main article (Delmas and Burbano, 2011).

We began by examining the collaboration network among authors based on their countries of origin to identify global scientific interest in greenwashing by geographic area. We established a minimum threshold of 30 papers from the same country and out of a total of 116 countries in the sample, 27 were selected for analysis. The size of the nodes representing each country reflects its significance in greenwashing research. The thickness of the connecting lines and the distance between nodes indicate the strength of collaboration among authors. The graphical representation demonstrates five distinct clusters of countries, each represented in a different color, grouped according to the intensity of scientific collaboration.

The most significant country for international collaboration is China, which is part of the first cluster (red). Chinese authors predominantly collaborated with authors and institutions from India, South Korea, Australia, Finland, Iran, Japan and others, as shown in Figure 7.

Figure 7
A network visualization shows collaboration linkages among author connections by country of origin.The network displays multiple clusters of nodes, each represented by circles with labels, connected by thin lines indicating relationships, with labels adjacent to the nodes. At the center-right, a large red node labeled “peoples r china” is directly connected to the red nodes on the bottom left labeled as follows: “iran,” “australia,” “malaysia,” “indonesia,” “south korea,” “japan,” “thailand,” “taiwan,” and “india.” On the center top and center bottom, two purple nodes are present and labeled “canada” and “u s a.” In between them, three purple nodes are present and labeled as follows: “turkey,” “pakistan,” and “england.” On the bottom right, green node clusters are present and labeled as follows: “netherlands,” “italy,” “germany,” “france,” “spain,” “sweden,” “belgium,” “brazil,” and “portugal.” On the top left, three yellow nodes are present and labeled as follows: “egypt,” “poland,” and “saudi arabia.”

Network of author connections by country of origin. Source: Authors’ processing using VOSviewer

Figure 7
A network visualization shows collaboration linkages among author connections by country of origin.The network displays multiple clusters of nodes, each represented by circles with labels, connected by thin lines indicating relationships, with labels adjacent to the nodes. At the center-right, a large red node labeled “peoples r china” is directly connected to the red nodes on the bottom left labeled as follows: “iran,” “australia,” “malaysia,” “indonesia,” “south korea,” “japan,” “thailand,” “taiwan,” and “india.” On the center top and center bottom, two purple nodes are present and labeled “canada” and “u s a.” In between them, three purple nodes are present and labeled as follows: “turkey,” “pakistan,” and “england.” On the bottom right, green node clusters are present and labeled as follows: “netherlands,” “italy,” “germany,” “france,” “spain,” “sweden,” “belgium,” “brazil,” and “portugal.” On the top left, three yellow nodes are present and labeled as follows: “egypt,” “poland,” and “saudi arabia.”

Network of author connections by country of origin. Source: Authors’ processing using VOSviewer

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The analysis of international collaboration networks conducted with VOSviewer reveals a notable shift in global concerns about greenwashing, particularly during the COVID-19 pandemic. Figure 8 illustrates significant differences in the chronological distribution of countries’ interests in this topic. During the pre-pandemic period (2016–2019), research and discussions on greenwashing were primarily concentrated in the Western world, particularly in the USA, the United Kingdom, Germany, France and other Western European nations. These countries, represented by violet-blue nodes in the network visualization, played a key role in voicing criticism against misleading sustainability practices promoted by companies. In contrast, the post-pandemic period (2020–2024) has witnessed a geographical expansion of concerns regarding greenwashing. Nations such as China, India, Iran, Saudi Arabia, Malaysia and Brazil, marked in green to yellow, have become more active in this field, indicating a growing interest in recent years.

Figure 8
A network visualization shows the temporal and geographical evolution of greenwashing.The network displays multiple clusters of nodes, each represented by circles with labels, connected by thin lines indicating relationships, with labels adjacent to the nodes. A scale bar at the bottom right shows a color gradient transitioning from blue to yellow. The blue represents “2016,” and in increments of 2, the color transitions until the yellow represents “2024.” At the center-right, a large node labeled “peoples r china” is directly connected to the nodes on the bottom left labeled as follows: “iran,” “australia,” “malaysia,” “indonesia,” “south korea,” “japan,” “thailand,” “taiwan,” and “india.” On the center top and center bottom, nodes are present and labeled “canada” and “u s a.” In between them, three nodes are present and labeled as follows: “turkey,” “pakistan,” and “england.” On the bottom right, node clusters are present and labeled as follows: “netherlands,” “italy,” “germany,” “france,” “spain,” “sweden,” “belgium,” “brazil,” and “portugal.” On the top left, three nodes are present and labeled as follows: “egypt,” “poland,” and “saudi arabia.”

Temporal and geographical evolution of greenwashing. Source: Authors’ processing using VOSviewer

Figure 8
A network visualization shows the temporal and geographical evolution of greenwashing.The network displays multiple clusters of nodes, each represented by circles with labels, connected by thin lines indicating relationships, with labels adjacent to the nodes. A scale bar at the bottom right shows a color gradient transitioning from blue to yellow. The blue represents “2016,” and in increments of 2, the color transitions until the yellow represents “2024.” At the center-right, a large node labeled “peoples r china” is directly connected to the nodes on the bottom left labeled as follows: “iran,” “australia,” “malaysia,” “indonesia,” “south korea,” “japan,” “thailand,” “taiwan,” and “india.” On the center top and center bottom, nodes are present and labeled “canada” and “u s a.” In between them, three nodes are present and labeled as follows: “turkey,” “pakistan,” and “england.” On the bottom right, node clusters are present and labeled as follows: “netherlands,” “italy,” “germany,” “france,” “spain,” “sweden,” “belgium,” “brazil,” and “portugal.” On the top left, three nodes are present and labeled as follows: “egypt,” “poland,” and “saudi arabia.”

Temporal and geographical evolution of greenwashing. Source: Authors’ processing using VOSviewer

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This phenomenon can be attributed to several factors, including increased international pressure on governments and companies to implement genuine sustainability policies, a rising demand for transparency in ESG reporting and changing consumer perceptions following the pandemic. These shifts have underscored the vulnerabilities in global systems and highlighted the importance of environmental protection. This shift in time and geography indicates that greenwashing is now viewed as a global issue, not limited to the Western context. This change has significant implications for how sustainability is practiced and communicated worldwide, as illustrated in Figure 8.

Table 1 presents a comprehensive overview of the countries that are most pertinent to the field of greenwashing research. These countries are systematically organized in descending order, reflecting the strength of their interconnections with other nations in this domain.

Table 1

Countries actively engaged in greenwashing research

CountryDocumentsCitationsTotal link strength
China84518.418159
The USA36311.834119
England1203.54070
India2004.35855
Germany1343.45651
Spain1503.27150
Saudi Arabia591.29949
Australia863.21949
Canada1033.75549
Italy1394.01849
France792.00240
South Korea903.00739
Egypt742.39627
Brazil842.28525
Pakistan5376622
The Netherlands411.63720
Iran1233.47019
Malaysia441.08419
Taiwan5297719
Belgium311.07317
Japan751.73316
Portugal4586715
Poland4080113
Thailand341.08013
Sweden3794712
Turkey421.33410
Indonesia301636
Source(s): Authors’ processing using VOSviewer

In our analysis, we examined the connections between co-authors and organizations, as shown in Figure 9. We established a minimum requirement of 15 documents and 15 citations for each organization. As a result, out of 3,318 organizations, only 14 met these criteria. The VOSviewer network analysis has identified a significant concentration of greenwashing research at Chinese universities. Prominent institutions like the Chinese Academy of Sciences and Tsinghua University serve as key nodes within this network, indicating a research direction that aligns with national sustainability policies. While there are fewer collaborations with international organizations, these connections demonstrate the field’s willingness to embrace a global perspective.

Figure 9
A figure shows a network map with 9 nodes.The network displays 9 clusters of nodes, each represented by circles with labels, connected by thin lines indicating relationships, with labels adjacent to the nodes. Starting from the large red node on the left labeled “chinese acad sci,” which is connected to another red node present below it labeled “univ chinese acad sci” with a thick red line. “chinese acad sci” is also connected to a small red node on the far right labeled “islamic azad univ.” On the top left, three green nodes are present. The large green node is labeled “hong kong polytech univ,” and the other two nodes are labeled as follows: “tsinghua a univ” and “sichuan univ.” On the bottom left, three blue nodes are shown. The largest is labeled “wuhan text univ,” and the other two are labeled “soochow ow univ” and “donghua univ.”

Network of co-author and organization connections. Source: Authors’ processing using VOSviewer

Figure 9
A figure shows a network map with 9 nodes.The network displays 9 clusters of nodes, each represented by circles with labels, connected by thin lines indicating relationships, with labels adjacent to the nodes. Starting from the large red node on the left labeled “chinese acad sci,” which is connected to another red node present below it labeled “univ chinese acad sci” with a thick red line. “chinese acad sci” is also connected to a small red node on the far right labeled “islamic azad univ.” On the top left, three green nodes are present. The large green node is labeled “hong kong polytech univ,” and the other two nodes are labeled as follows: “tsinghua a univ” and “sichuan univ.” On the bottom left, three blue nodes are shown. The largest is labeled “wuhan text univ,” and the other two are labeled “soochow ow univ” and “donghua univ.”

Network of co-author and organization connections. Source: Authors’ processing using VOSviewer

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Table 2 presents the key organizations involved in greenwashing research, ranked in order of their connections with other institutions.

Table 2

Organizations involved in greenwashing research

OrganizationDocumentsCitationsTotal link strength
Chinese Academy of Science471.19021
Wuhan Textile University224099
Tsinghua University211.0397
Hong Kong Polytechnic University211.2897
Soochow University389776
Sichuan University232794
Donghua University338182
Islamic Azad University238321
Consejo Superior de Investigaciones Cientificas – CSIC204520
Jiangnan University253260
National Research Center301.3690
University of Ljubljana157160
Zhejiang Sci-Tech University182630
Source(s): Authors’ processing using VOSviewer

We examined the connections between scientific journals based on the shared references in their articles, as illustrated in Figure 10. We established a minimum requirement of 15 documents and 15 citations for each source. Out of 1,339 total sources, only 21 met these criteria. The stronger the connection between two journals, the more references they share. Notably, the Journal of Cleaner Production serves as the central hub in the literature on greenwashing, being both the most cited and the most interconnected journal in this field.

Figure 10
A bibliographic coupling network with clusters for cleaner production journals and food safety journals.The network displays multiple clusters of nodes, each represented by circles with labels, connected by thin lines indicating relationships, with labels adjacent to the nodes. At the center-left, a large red node labeled “journal of cleaner production” is directly connected to the red nodes on the left labeled as follows: “scientific reports,” “a c s sustainable chemistry and e n,” and “r s c advance.” On the right side, two green nodes are shown labeled as follows: “food control” and “journal of food protection.” The two main clusters are connected by thinner lines.

Network of bibliographic coupling by source. Source: Authors’ processing using VOSviewer

Figure 10
A bibliographic coupling network with clusters for cleaner production journals and food safety journals.The network displays multiple clusters of nodes, each represented by circles with labels, connected by thin lines indicating relationships, with labels adjacent to the nodes. At the center-left, a large red node labeled “journal of cleaner production” is directly connected to the red nodes on the left labeled as follows: “scientific reports,” “a c s sustainable chemistry and e n,” and “r s c advance.” On the right side, two green nodes are shown labeled as follows: “food control” and “journal of food protection.” The two main clusters are connected by thinner lines.

Network of bibliographic coupling by source. Source: Authors’ processing using VOSviewer

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Table 3 lists the primary journals that concentrate on studies related to greenwashing.

Table 3

Leading journals in greenwashing research

SourceDocumentsCitationsTotal link strength
Journal of Cleaner Production803.6411036,02
Sustainability801.231973,40
Business Strategy and the Environment271.096739,78
Environment, Development and Sustainability28208605,71
Corporate Social Responsibility and Environmental Management15492472,93
Environmental Science and Pollution Research32461371,13
Science of the Total Environment24656163,33
Journal of Environmental Management15265156,72
ACS Sustainable Chemistry and Engineering321.326139,13
Scientific Reports1528146
Source(s): Authors’ processing using VOSviewer

We examined the distribution of the most frequently used keywords to analyze their relationships, focusing only on those provided by authors in published works. We established a minimum threshold of 50 co-occurrences. Out of 3,004 works, we identified 14,564 keywords, with 33 surpassing the established threshold.

Keyword clusters that appear together in the same paper are represented in the same color. Figure 11 illustrates the relevance of each keyword through nodes, where the size of the node indicates its importance; larger nodes represent more significant terms within the sample. The connections between nodes are shown as curved lines, which indicate the frequency of co-occurrence for the linked terms. The thicker the line, the more frequently the two terms appear together. Additionally, a shorter curve indicates a stronger relationship between the two terms. We identified three distinct keyword clusters. The red cluster comprises the most keywords related to greenwashing. The largest node in this group corresponds to performance. Over time, greenwashing can harm a company’s reputation and credibility, significantly impacting its performance relative to competitors, investors and consumers.

Figure 11
A Network map with red clusters on greenwashing and performance, linked to single nodes, vegetables, and green chemistry.The network displays multiple clusters of nodes, each represented by circles with labels, connected by thin lines indicating relationships, with labels adjacent to the nodes. On the bottom left, four large red nodes are labeled “greenwashing,” “green,” “management,” and “performance,” which are connected to other red nodes labeled as follows: “products,” “growth,” “degradation,” “optimization,” “quality,” “water,” “removal,” “extraction,” “consumption,” “adsorption,” “nanoparticles,” “consumers,” “acid,” “green synthesis,” “antibacterial,” “trust,” “disclosure,” “impact,” “behavior,” “silver nanoparticles,” “environmental performance,” “cellulose,” “cotton,” “fibers,” and “textiles.” At the top left, a single green node is labeled “vegetables.” At the right, a single blue node is labeled “green chemistry.”

Network of keyword connections in greenwashing research. Source: Authors’ processing using VOSviewer

Figure 11
A Network map with red clusters on greenwashing and performance, linked to single nodes, vegetables, and green chemistry.The network displays multiple clusters of nodes, each represented by circles with labels, connected by thin lines indicating relationships, with labels adjacent to the nodes. On the bottom left, four large red nodes are labeled “greenwashing,” “green,” “management,” and “performance,” which are connected to other red nodes labeled as follows: “products,” “growth,” “degradation,” “optimization,” “quality,” “water,” “removal,” “extraction,” “consumption,” “adsorption,” “nanoparticles,” “consumers,” “acid,” “green synthesis,” “antibacterial,” “trust,” “disclosure,” “impact,” “behavior,” “silver nanoparticles,” “environmental performance,” “cellulose,” “cotton,” “fibers,” and “textiles.” At the top left, a single green node is labeled “vegetables.” At the right, a single blue node is labeled “green chemistry.”

Network of keyword connections in greenwashing research. Source: Authors’ processing using VOSviewer

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Figure 12 presents an overlay visualization that highlights the temporal distribution of keywords within each cluster. In this view, keywords are color-coded based on a score derived from their average year of appearance. During the pre-pandemic period, the focus was on ethical and managerial assessments of greenwashing. However, with the onset of the pandemic, technical and scientific terms began to emerge, indicating a growing integration of sustainability into technology and industrial processes. Most recently, after 2023, the term “greenwashing” has increasingly been linked to behavioral aspects and impacts, indicating a renewed interest in public perception and regulation.

Figure 12
A temporal evolution network of greenwashing showing changing connections with key terms over time.The network displays multiple clusters of nodes, each represented by circles with labels, connected by thin lines indicating relationships, with labels adjacent to the nodes. A scale bar at the bottom right shows a color gradient transitioning from blue to yellow. The blue represents “2016,” and in increments of 2, the color transitions until the yellow represents “2024.” On the bottom left, four large nodes are labeled “greenwashing,” “green,” “management,” and “performance,” which are connected to other red nodes labeled as follows: “products,” “growth,” “degradation,” “optimization,” “quality,” “water,” “removal,” “extraction,” “consumption,” “adsorption,” “nanoparticles,” “consumers,” “acid,” “green synthesis,” “antibacterial,” “trust,” “disclosure,” “impact,” “behavior,” “silver nanoparticles,” “environmental performance,” “cellulose,” “cotton,” “fibers,” and “textiles.” At the top left, a single green node is labeled “vegetables.” At the right, a single node is labeled “green chemistry.”

Temporal evolution of greenwashing in relation to key terms. Source: Authors’ processing using VOSviewer

Figure 12
A temporal evolution network of greenwashing showing changing connections with key terms over time.The network displays multiple clusters of nodes, each represented by circles with labels, connected by thin lines indicating relationships, with labels adjacent to the nodes. A scale bar at the bottom right shows a color gradient transitioning from blue to yellow. The blue represents “2016,” and in increments of 2, the color transitions until the yellow represents “2024.” On the bottom left, four large nodes are labeled “greenwashing,” “green,” “management,” and “performance,” which are connected to other red nodes labeled as follows: “products,” “growth,” “degradation,” “optimization,” “quality,” “water,” “removal,” “extraction,” “consumption,” “adsorption,” “nanoparticles,” “consumers,” “acid,” “green synthesis,” “antibacterial,” “trust,” “disclosure,” “impact,” “behavior,” “silver nanoparticles,” “environmental performance,” “cellulose,” “cotton,” “fibers,” and “textiles.” At the top left, a single green node is labeled “vegetables.” At the right, a single node is labeled “green chemistry.”

Temporal evolution of greenwashing in relation to key terms. Source: Authors’ processing using VOSviewer

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Table 4 presents the 15 keywords with the highest linkage strength to other keywords, indicating their most frequent co-occurrence. For example, the frequent co-appearance of the keywords “greenwashing” and “performance” suggests a strong conceptual correlation between them.

Table 4

Key terms used by authors in greenwashing research

KeywordOccurrencesTotal link strength
Performance193322
Sustainability183306
Impact106205
Disclosure78202
Management89180
Corporate social responsibility69169
Environmental performance62169
Green synthesis111164
Consumers53113
Quality79104
Degradation6572
Products5268
Growth5659
Optimization5655
Green chemistry5426
Source(s): Authors’ processing using VOSviewer

It is generally assumed that ESG disclosure provides valuable, transparent, impartial and high-quality information regarding a company’s sustainability efforts, which can help reduce market mispricing. However, there is also the risk of ESG greenwashing. Unlike financial reports, ESG reports are not completely assured so far and lack standardized formatting requirements, allowing for significant managerial discretion. In such cases, ESG disclosure can become a tool that managers use to enhance the company’s image and persuade stakeholders of their commitment to environmental responsibility. This can attract more investments and improve the company’s valuations (Chen and Dagestani, 2023).

ESG greenwashing refers to the misleading corporate practice of presenting information that superficially addresses external pressures, while failing to deliver genuine improvements in ESG performance (Yu et al., 2020; Zhang, 2022; Chen and Dagestani, 2023). This practice adds unnecessary complexity to informational environments, which is critical for investor decision-making. Furthermore, in industries characterized by less competition and weaker environmental regulations, publicly listed companies are more likely to engage in ESG greenwashing, potentially leading to mispriced stock values (Lin et al., 2023).

Companies motivated by profit maximization may engage in greenwashing behaviors. Additionally, when a company chooses to issue bonds, it benefits from government tax incentives, which can further encourage greenwashing practices (Sun and Zhang, 2019). To promote sustainability, many countries incentivize companies to enhance their environmental commitment by providing various benefits, particularly tax incentives such as tax credits or deductions (Yu et al., 2021). For instance, firms that invest in clean technologies can receive tax credits, while those that adopt eco-friendly practices and improve their greenhouse gas emission reporting may benefit from tax reductions. In the similar view, Umar et al. (2025) highlight that rising temperatures will exacerbate financial vulnerabilities, particularly in the textile and natural gas sectors, which could increase non-performing loans and variable default probabilities. Banks should include climate risk assessments in their financial management frameworks, taking these risks into account.

The European Banking Authority (EBA, 2021) recommends that financial institutions incorporate ESG factors into their strategies and internal governance mechanisms. They suggest that remuneration policies should be aligned with ESG objectives. Recently, major institutional investors (Lu, 2023) have emphasized the importance of selecting companies that include ESG criteria in their executive compensation agreements. Since 2020, an increasing number of senior corporate leaders worldwide have had ESG objectives added to their compensation packages (Cohen et al., 2023; Lu, 2023). Finally, Gaia Soana (2024) is the first to demonstrate in the literature that when banks adopt ESG contracting, it not only enhances their ESG performance but also leads to an increase in the number of ESG disputes. This suggests that this compensation practice may be more symbolic than substantial in addressing stakeholders’ interests, as indicated by Liu et al. (2024).

Before the COVID-19 pandemic, greenwashing primarily centered on broad concepts such as “eco-friendly,” “biodegradable” and “sustainable,” often lacking concrete or standardized evidence. Companies typically focused on specific product attributes, like “green” packaging and “natural” ingredients, appealing to consumers who were concerned about environmental issues. However, after the pandemic, greenwashing experienced a significant shift. The global context underscored the importance of social responsibility and climate resilience. Nowadays, businesses do not just promote isolated “green” products; they position their entire business models as sustainable. This is reflected in their use of more complex terms such as “carbon neutrality,” “net-zero emissions,” “circular economy” and “diversity and inclusion” as part of their ESG reporting.

The evolution of discourse surrounding greenwashing signifies a maturation in the field, accompanied by increasingly sophisticated manipulation tactics in response to heightened scrutiny from regulators, investors and civil society. This transition represents a shift from superficial assertions concerning individual products to the establishment of systemic commitments and intricate marketing strategies that are now embedded within corporate frameworks. Concurrently, the risk of facing sanctions has escalated. The phenomena of ESG fraud generate significant negative externalities, which include loss of market capitalization, legal repercussions, the withdrawal of financial partners and potentially irreversible harm to a corporation’s reputational capital. Such consequences underscore the critical importance of genuine commitment to sustainable practices within corporate entities. In this context, it is essential for policymakers to adopt a more coherent and stricter regulatory framework regarding non-financial reporting. First and foremost, the extension of external audit obligations for ESG reports is necessary, so that they are verified by independent entities according to transparent methodologies. Additionally, the development of proportional sanctioning mechanisms to penalize false or misleading declarations of environmental performance is crucial to discourage greenwashing. Finally, it is proposed to strengthen environmental literacy among consumers and investors through awareness campaigns supported by public institutions, so that economic decisions are based on genuine sustainability criteria rather than artificially constructed images.

One significant limitation of this research is its predominant reliance on bibliometric and network analysis through the use of VOSviewer, which necessitates the employment of standardized scientific databases. This methodological framework may inadvertently exclude pertinent non-academic sources, such as internal company reports and recent journalistic investigations, thereby constraining the comprehensiveness of the perspective on the contemporary phenomenon of greenwashing. Additionally, the existing body of literature on greenwashing tends to discuss the subject in relatively generalized terms, often lacking a detailed differentiation between sector-specific manifestations (for instance, greenwashing within the fashion industry compared to the energy sector) or typologies of greenwashing (such as unintentional versus deliberate greenwashing). This thematic homogenization may further diminish the depth and specificity of the analysis.

To enhance future research, it is suggested that further studies include in-depth case studies or interviews with relevant stakeholders, including companies, non-governmental organizations (NGOs) and regulatory bodies. Such an approach would facilitate a richer understanding of the contextual nuances and intentionality underlying acts of greenwashing, thereby contributing to a more comprehensive examination of the phenomenon.

This study did not involve human participation or animal experiments.

This article is part of the research project “The Synergistic Effect of Key Factors in Sustainable Development in the ECO Region”, funded by the Agence Universitaire de la Francophonie in Central and Eastern Europe (AUF – ECO), within the framework of the call for projects “Support for Francophone Scientific Research in Central and Eastern Europe – RESCI-ECO – 2024 Call for Projects” by AUF ECO.

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