Challenging to Change? Examining the Link Between Public Participation and Greenwashing Based on Organizational Inertia

Abstract

This study investigates the impact of public participation on corporate greenwashing behavior among listed companies in China from 2011 to 2019, set against a backdrop of increasing global environmental regulations. Corporate greenwashing, characterized by misleading environmental claims, poses a significant barrier to sustainable development. Despite the recognition of public participation in social governance, organizational inertia often prevents companies from responding effectively. Our analysis reveals that public participation leads to stricter environmental regulations, thereby reducing greenwashing practices. This finding remains robust through various tests, including variable substitution and model adjustments. However, we also find that higher levels of organizational inertia weaken the positive influence of public participation on combating greenwashing. Thus, this study underscores the necessity of establishing mechanisms for public participation that can effectively shape corporate decision-making, offering crucial insights for enhancing corporate accountability and advancing sustainable practices.

1. Introduction

Against the backdrop of intensifying global environmental regulations, green sustainability and corporate social responsibility (CSR) have become the core themes of market competition. This trend arises not only from the cultivation and guidance of environmental regulations on consumers’ environmental awareness but also reflects society’s deep expectation for enterprises to fulfill their environmental responsibilities. However, despite the favorable market environment, enterprises encounter numerous difficulties in shifting towards greener production methods. On the one hand, during the initial stage of green transformation, enterprises need to invest substantial amounts of capital in equipment renewal, technological research and development, and process reengineering, which is a heavy economic burden for them. For instance, as shown in the research by Huang Mingzhi et al. [1], in 2019, China’s CO₂ emissions accounted for approximately 27% of the global total, prompting the Chinese government to formulate carbon peaking and carbon neutrality goals, with enterprises facing stricter requirements for carbon emission performance as a result. When responding to these policies, enterprises not only have a large capital demand for purchasing environmental protection equipment and conducting technological research and development but are also restricted by other factors, such as talent shortages and long research and development cycles, resulting in slow progress in their green transformation. On the other hand, different stakeholders have significantly different expectations and requirements regarding corporate environmental protection measures. Consumers focus on the environmental attributes of products, investors value the economic benefits of environmental protection investments, and regulatory agencies emphasize compliance with regulations. These differences make it difficult for enterprises to coordinate the interests of all parties and fulfill their environmental responsibilities, thus giving rise to and spreading the phenomenon of greenwashing [2]. Corporate “greenwashing” behavior refers to the act of companies falsely or exaggeratedly promoting that they possess environmental awareness. This behavior severely disrupts the fairness of market competition, misleads consumers, weakens public trust, and significantly hampers the dissemination of the concept of green development and the advancement of sustainable development strategies. It is a major threat to the transformation of the green economy and ecological environment protection [3,4,5]. Such behavior not only erodes the trust foundation of consumers and other stakeholders but also destroys the ecological environment of fair competition in the market and violates the principles of fairness and honesty upheld by environmental regulations. From a market impact perspective, the proliferation of greenwashing behavior triggers consumers’ doubts about the authenticity of environmental communication, suppressing their willingness to purchase truly environmentally friendly products. Meanwhile, investor confidence in enterprises is undermined, leading to a decline in enterprise market value, casting a shadow over the long-term development prospects of enterprises, and enterprises may also face the risk of severe penalties under environmental regulations.

From the perspective of academic research, the study of corporate greenwashing mainly focuses on the internal motivation of the organization (e.g., cost control considerations and perceived institutional pressure) and external drivers (e.g., government regulation and market competition). Institutional pressure theory reveals the critical role of external pressure sources, including the mandatory constraints of laws and regulations and the soft guidance of social norms, in corporate behavioral decisions. For example, when a firm violates environmental regulations and commits a crime, it will face criminal liability. As argued by Ciabuschi et al. [6], despite the compliance costs associated with environmental regulations, they also serve as a powerful driver of firms’ technological innovations, prompting firms to improve output efficiency and achieve cost compensation, highlighting the core value of institutional pressures in guiding the trajectory of firms’ environmental behavior. In addition, Delmas, Magali A. et al. [7] show that under the dominant environmental regulatory pressure of government regulation, firms tend to adopt selective disclosure, positive disclosure, imitation, and linguistic modification of environmental information disclosure strategies to maintain their legitimacy, highlighting the potential influence of social norms as a specific form of institutional pressure on firms’ behavioral decision-making process.

At the same time, stakeholder theory emphasizes the strong influence of the public as a core stakeholder of the enterprise, i.e., the role of public participation. Public participation originates from the Western modern public governance theory. In the construction of ecological civilization, the public, with multiple identities, such as consumers, community members, investors, environmental advocates, and social supervisors, intervenes in the formulation of corporate strategic decision-making through expressing consumer preferences, releasing the power of public opinion supervision and operating the social evaluation mechanism [8,9]. For example, some scholars have pointed out through research that negative media coverage leads to an increase in green investments by companies, and a corresponding decrease in pollutant emissions [10]. Under the macro framework of environmental regulation, public participation can effectively prompt the government and regulatory agencies to implement stricter control measures on corporate greenwashing behavior based on environmental regulatory requirements. In order to maintain good public relations, enhance market competitiveness, and avoid social resistance and legal risks, enterprises must pay full attention to public opinions and interests.

However, the current research also reveals that there are obvious limitations in the public’s ability to identify real environmental initiatives and greenwashing behaviors. In the absence of external policy interventions (especially the refinement and reinforcement of environmental regulatory policies), companies often lack the intrinsic motivation to voluntarily disclose their true level of environmental commitment, which to a large extent limits the effective influence of public participation on corporate decision-making. In addition, evolutionary economics and path dependence theory state that organizations adapt to environmental changes through mechanisms, such as search, inertial adjustment, and selection [11]. Path dependence theory further suggests that a firm’s past successes may lead it to fall into path lock-in with established methods, even if these traditional methods are no longer optimal under new environmental conditions [12]. Therefore, enterprises which have relied on non-green production methods for a long time often find it difficult to achieve a smooth transition to green strategies due to organizational inertia. The stronger the organizational inertia, the more difficult it is for enterprises to break away from tradition and achieve a truly green transformation, and, thus, they are more inclined to choose the low-cost and short-term benefits of greenwashing strategies, which is in stark contrast to the goal of positive green transformation of enterprises advocated by environmental regulations.

Given that environmental sustainability has become a central focus in all areas of society, its impact on corporate behavior will continue to deepen over time [13,14]. Despite the imminent need for companies to shift to greener production methods, the upfront investment and technological innovation thresholds required, as well as the multiple expectations and needs of different stakeholders, are intertwined in the context of environmental regulation, constituting an extremely complex economic and social landscape. In this context, in order to effectively promote corporate environmental responsibility and reduce greenwash behavior, it is necessary to comprehensively consider various factors.

This study will focus on the following key dimensions. First, we will analyze the role of public participation in corporate greenwashing behavior. Gray et al. (2020) pointed out that the public has limited ability to distinguish between genuine environmental initiatives and greenwashing behavior, which to some extent reduces the perceived risk of corporate greenwashing behavior [15]. Moreover, without external policy interventions (including environmental regulatory policies), firms are extremely reluctant to proactively disclose their true level of environmental commitment. Therefore, this study argues that public participation can effectively combat corporate greenwash by pressuring governments and regulatory agencies to enact stricter measures based on environmental regulations. Widespread and in-depth public participation plays a crucial role in curbing corporate greenwashing.

Secondly, this study will explore the intrinsic connection between public participation and corporate greenwashing and will suggest that public participation can be regarded as a unique social normative pressure, which has a supplementary value in restraining corporate greenwashing from the perspective of the informal system. Nevertheless, detailed and systematic research on public participation in regulating corporate greenwashing remains lacking, especially research on how public participation works. This study is dedicated to filling the research gap in this key area by systematically analyzing the interrelationship between public participation, environmental regulation, organizational inertia, and other factors, to reveal the driving mechanisms and constraints behind corporate greenwashing behavior, and to provide novel perspectives and solid theoretical support for the construction of a more complete and efficient corporate environmental behavioral constraints system. This is an effective expansion and deepening of the research in this field, which helps to further enrich and improve the theoretical system of corporate environmental behavior research, and it provides a more targeted and scientific theoretical basis and decision-making reference for the formulation of relevant policies (especially environmental regulation policies) and corporate practice.

Finally, this study is of significance to the study of sustainable development. By exploring the role of public participation in corporate greenwashing and its relationship with environmental regulation and organizational inertia, we can pinpoint the key factors affecting corporate sustainable development. By revealing the complex mechanisms behind corporate greenwashing, we can help companies avoid reputation damage, legal disputes (violation of environmental regulation laws), and other negative consequences of falling into greenwashing misconceptions, thus providing a strong guarantee for companies to move forward on the road of green development and directly assisting in the construction and implementation of corporate sustainable development strategies. At the same time, clarifying the importance of public participation and the influence of organizational inertia can guide corporate stakeholders and the public to focus on the substance of corporate environmental actions, avoid being misled by superficial green marketing, and promote the implementation of corporate environmental protection strategies, which is compatible with the ultimate goal of environmental regulation. In addition, the results of this research can provide the media and other external stakeholders with a theoretical basis and supervisory focus, so that they can more effectively play a supervisory and guiding role in the process of sustainable development, and prompt the government, enterprises, and other parties to actively fulfill the goals and responsibilities of sustainable development under the norms and constraints of environmental regulation, so as to jointly build a green social ecology of sustainable development.

2. Theoretical Analysis and Hypothesis Development

2.1. Public Participation and Corporate Greenwashing

Bowen et al. (2014) argued that greenwashing represents a form of symbolic environmental behavior by companies, characterized by actions that lack substantial environmental impact [16]. Similarly, Lyon and Maxwell (2011) described greenwashing as an information management strategy, where companies selectively disclose positive environmental information while concealing negative aspects [17]. Kim et al. (2017) proposed that corporate environmental responsibility is an organic unity of moral and legal obligations [18]. Thus, greenwashing behavior involves not only meeting legal requirements but also addressing the public’s expectations for companies to fulfill their social responsibilities [19]. Research on the factors influencing corporate greenwashing has primarily focused on internal corporate dynamics, such as awareness of corporate social responsibility, market competition pressures, and decision-maker characteristics. For example, Karaman et al. (2021) suggested that when decision-makers underestimate the public’s ability to verify corporate disclosures, opportunistic behavior can thrive, leading to widespread greenwashing [20]. Studies that examine external influences often focus on stakeholders, with Nardi (2022) noting that consumer demand for green products incentivizes companies to engage in green practices. However, due to consumers’ limited ability to assess the quality of corporate disclosures, opportunities for greenwashing arise [21]. While these studies provide a foundation for understanding corporate greenwashing, they have often overlooked the public as a key stakeholder. Public participation plays a crucial role in monitoring corporate decision-making, making it essential to consider in studies of corporate greenwashing.

The term “public participation” originates from modern Western theories of public governance and refers to the active participation of individuals or groups in public policy making, public affairs management and public life through a variety of means [22]. There are various forms of such participation, including public hearings, citizens’ juries, and advisory panels [23,24,25]. The aim is to promote sustainable decision-making and democratic governance of public affairs by providing channels and information for the public to participate in public life and influence public policy. In China, the National People’s Congress (NPC) proposal system provides an example of public participation influencing social governance. Through this system, NPC deputies and members of the Chinese People’s Political Consultative Conference (CPPCC) collect public opinions on environmental governance and compile them into proposals for consideration [26]. These proposals, if approved, are submitted to relevant agencies for action, thereby influencing decision-making.

Scholars have increasingly recognized the positive role of public participation in encouraging corporate sustainability. Zhang et al. (2023) found that public participation in environmental governance can reduce corporate environmental violations [27]. Hamouda and Aissaoui (2024) demonstrated that public involvement strengthens environmental regulations and investments in pollution control, with rising environmental awareness encouraging consumers to prefer green products [28]. To meet public demands and gain a competitive advantage, companies may reduce their greenwashing activities. Therefore, public participation plays multiple roles—guiding, supervising, and supporting—in influencing corporate greenwashing, serving as a driving force for companies to adopt sustainable practices. Based on these insights, we hypothesize the following:

H1: 

Higher levels of public participation are negatively associated with the incidence of corporate greenwashing.

2.2. Public Participation, Environmental Regulation and Corporate Greenwashing

Environmental regulation encompasses laws, policies, and standards that control the environmental impacts of economic and social development [29]. Its role in promoting sustainable development is well-recognized. First, environmental regulations protect ecosystems and human health by setting emission standards and improving waste management [30]. Second, strict regulations compel companies to adopt environmentally friendly technologies, driving innovation [31]. Furthermore, the study by Yang and Tang (2023) reinforces the positive impact of environmental regulation on social welfare [32], while Li et al. (2022) argue that regulation prevents firms from gaining an unfair advantage at the expense of the environment [33].

Public participation, as both environmental advocates and consumers, significantly influences stakeholders involved in formulating environmental policies [34]. The public can drive policy development by engaging in lobbying activities and participating in public hearings, ensuring stricter, more effective regulations that reduce corporate greenwashing [22,35]. Furthermore, public participation promotes fair enforcement, as environmental organizations and the public can take legal action to hold companies accountable for greenwashing [36], deterring others from engaging in similar practices. Based on these considerations, we propose the following hypothesis:

H2: 

Public participation influences corporate greenwashing through its effect on environmental regulation. Specifically, (a) public participation will relate positively to environmental regulation and (b) environmental regulation will relate negatively to corporate greenwashing.

2.3. Public Participation, Organizational Inertia, and Corporate Greenwashing

Organizational inertia refers to an organization’s tendency to continue operating in its usual manner, resisting changes in response to environmental shifts [37]. It reflects an organization’s inclination to maintain the status quo rather than adopt strategic changes [38]. Scholars have long discussed the impact of inertia on organizational survival and development. Tjahjadi et al., (2024) noted that inertia locks companies into established cognitive and institutional structures, hindering innovation [39]. On the other hand, Wei et al. (2011) suggested that inertia can help organizations adapt to changes in their environment, viewing it as a form of resilience [40]. Girod and Whittington (2017) found that, during periods of rapid technological change, inertia can provide stability and consistency in decision-making [41]. Following studies by Finkelstein and Hambrick (1990) [42], and Lian and He (2015) [43], organizational inertia can be measured by analyzing the degree of fluctuation in the allocation of strategic resources over time. Minimal fluctuation indicates a higher degree of inertia, while significant fluctuation suggests a break from strategic inertia. Common indicators for measuring inertia include advertising expenditure, R&D expenditure, and financial leverage ratios, among others.

The concept of organizational inertia is crucial for understanding why companies often struggle to balance commercial and social values, even when they recognize the importance of environmental responsibility [44]. Vermeulen and Barkema (2002) emphasized that an organization’s ability to engage in new activities depends on its capacity to absorb new knowledge [45]. Additionally, implementing environmental responsibility strategies often requires structural changes within the organization [46], and the success of these strategies hinges on the extent to which organizational inertia resists or facilitates these changes. Therefore, we conducted a study on public participation and corporate greenwashing behavior from the perspective of organizational inertia. Our discussion posits that organizational inertia moderates the relationship between public participation and corporate greenwashing by influencing how companies respond to external pressures. Figure 1 presents our overall model. Our baseline hypothesis is as follows:

H3: 

Organizational inertia moderates the relationship between public participation and corporate greenwashing. High organizational inertia weakens the positive impact of public participation, making companies more likely to adopt greenwashing strategies. Conversely, low organizational inertia facilitates genuine environmental improvements in response to public participation.

Figure 1. Overall model of corporate greenwashing.

Figure 1. Overall model of corporate greenwashing.

3. Research Design

3.1. Data and Sample

This study selects companies listed in China’s Shanghai and Shenzhen A-share markets from 2011 to 2019 and draws its data from the China Securities Market and Accounting Research Database (CSMAR), which is widely recognized as a valid and reliable source of data in the field of academic research [47]. The data for this study are based on a broader research project that has been cited in previous academic studies, as shown, for example, in references [43,47]. Nevertheless, our study differs markedly from the research literature mentioned above. In terms of research direction, we focus specifically on the two core topics of public participation and corporate greenwashing, which differs from the focus of previous studies. In terms of theoretical foundation, we adopt social responsibility theory and stakeholder theory as the support of our study to examine the related issues from a brand-new perspective, aiming to contribute new perspectives and thoughts to the academic research in this field. The Shanghai and Shenzhen A-share markets are characterized by diverse types of enterprises, huge market influence, and relatively high information disclosure requirements. These characteristics make the Shanghai and Shenzhen A-share markets an ideal place to study corporate green behaviors (e.g., “greenwashing”). In 2010, the concept of “green development” was formally proposed in the Outline of the Twelfth Five-Year Plan for National Economic and Social Development. Since 2010, Chinese companies have gradually established the concept of low-carbon development, which makes the period from 2011 to 2019 a valuable sample period for this study. In the research process, this study fully references the research results of previous scholars (e.g., Zhang (2022) [47], Zhang (2023) [48]). Through rigorous sample screening and processing, we determined the final study sample. The specific processing steps are as follows.

Firstly, financial and insurance listed companies were excluded. The business characteristics of such companies are significantly different from those of other industries, and their financial structures and business models have particularities that may interfere with the research results. To ensure the homogeneity of the research sample, they were excluded. Secondly, listed companies in financial distress (such as those marked with ST) were removed. These enterprises are in a special financial situation, and their business decisions and behaviors may be severely affected by the financial crisis. They cannot represent the behavior patterns of normally operating enterprises and may lead to deviations in the research results. Thirdly, samples with missing relevant data should be excluded. The completeness of the data is crucial for the accuracy of the research. Missing data will affect the reliability of the model and the validity of the analysis results. In addition, some enterprises only have single-year data and lack continuity in the time series. Since this study uses panel data for econometric analysis, which requires data to have continuity in the time dimension to better capture the dynamic changes in enterprise behavior, the data from these enterprises were excluded. Finally, to eliminate the potential impact of extreme values on the research results, all continuous variables were Winsorized at the 1% and 99% quantiles. Extreme values may distort the statistical analysis results and lead to inaccurate model estimations. Through Winsorization, the data distribution can be made more reasonable, enhancing the robustness of the research results. After the above series of processing, a total of 6268 valid company observations were obtained as the final sample.

In this study, the data on firms drifting green are from the CSMAR database, and the proxies for the robustness tests are from the WIND database. As of 31 December 2019, there were 288 Shenzhen A-share listed companies and 298 Shanghai A-share listed companies in the Shanghai and Shenzhen A-share markets, respectively, widely distributed in multiple industries and fields, providing rich materials for constructing panel data at the Chinese listed company level. These data will be used for regression analysis in our subsequent econometric analysis to deeply explore the influencing factors and internal mechanisms behind corporate green behavior [49,50].

3.2. Independent Variable

In this paper, public participation is selected as the central independent variable, closely aligned with the unique institutional context of China, where suggestions from the National People’s Congress (NPC) and proposals from the Chinese People’s Political Consultative Conference (CPPCC) are regarded as significant reflections of public environmental opinions. Specifically, the public communicates with NPC delegates through letters and visits to express their environmental concerns; concurrently, CPPCC members are responsible for collecting public criticism and suggestions on environmental issues and conveying them to the government and relevant departments for action. Building on the research methodology of Long Wenbin et al. (2022) [51], this study confines its scope to the regional level, using the number of regional environmental protection-related NPC suggestions and CPPCC proposals as an indicator of public participation. This measure is standardized against the resident population of the province. A higher standardized value indicates a greater degree of public involvement in environmental affairs within the region and a stronger preference for environmental protection. This quantification approach not only helps to elucidate the impact of public participation on environmental policy but also provides policymakers with a scientific basis for assessing and comparing environmental awareness and levels of participation across different regions.

3.3. Dependent Variables

The relevant data for firms targeting greenwash were taken from (CSMAR), which is generally considered to be a valid and reliable source. We obtain information on subsidies granted from the WIND database and then manually match it with the firm ID and year. Regarding the design of the firms’ greenwashing variables, we follow Zhang (2022) [49] to assess the level of greenwashing through data from the Bloomberg ESG database and rating data from the China Securities Index Information Service (Huazheng database). We construct the Chinese firm-level panel data to rerun the external econometric analysis here. In terms of robustness testing, we conduct a relevant analysis through alternative indicators, and the specific variable design is as follows:

$$\begin{array}{c}Greenwashin{g}_{i,t}=\left[\left(ES{G}_{Disclosurei,t}-\overline{ES{G}_{Disclosurei,t}}\right)/{\sigma }_{ES{G}_{Disclosure}}\right]\\ -\left[\left(ES{G}_{Raitingi,t}-\overline{ES{G}_{Raitingi,t}}\right)/{\sigma }_{ES{G}_{Raiting}}\right]\end{array}$$

3.4. Intermediary Variable

In this study, environmental regulation is set as the mediating variable, which encompasses specific measures, such as laws, regulations, environmental standards, and prohibitions. Given that environmental regulations have a broad scope and impose comprehensive constraints on corporate environmental governance behaviors, this study adopts the research methodology of Chen Yunping et al. (2023) [52]. The research focuses on the regional level and utilizes the cumulative sum of environmental regulations in various provinces over the years as an indicator to evaluate the intensity of government command-and-control environmental regulations. This quantification approach aims to explore in depth how environmental regulations mediate the impact of public participation on corporate greenwashing behaviors and their potential role in enhancing corporate environmental responsibility and transparency.

3.5. Moderator Variable

This paper gauges organizational inertia through the concept of strategic inertia. Taking individual firms as the measurement level, strategic inertia is measured by assessing the degree of fluctuation in an organization’s strategic resource allocation over an annual period. If there is minimal fluctuation in strategic resource allocation within a year, it is considered that the strategic status quo is maintained, indicating a high degree of strategic inertia. Conversely, if there is significant fluctuation, it is regarded as evidence of strategic adjustments within the annual interval, suggesting that the strategic inertia has been broken. The measurement process of this indicator is as follows. Firstly, six dimensions of corporate strategic resources are obtained, namely (1) the ratio of advertising expenditure to sales revenue; (2) the ratio of R&D expenditure to sales revenue; (3) the ratio of net fixed assets to total fixed assets; (4) the ratio of unproductive expenditures to sales revenue; (5) the ratio of inventory to sales revenue; and (6) the financial leverage coefficient. Secondly, the variance $\sum {\displaystyle \frac{{\left({\mathrm{t}}_{\mathrm{i}}-\mathrm{T}\right)}^2}{\left[\mathrm{n}-1\right]}}$ of each of the above indicators over a five-year period (T − 1, T + 3) is measured using 2004, 2005, and 2006 as the base period T. Then, the obtained annual variance is standardized based on the industry and multiplied by minus one. Finally, the values of the six indicators after the above standardization and multiplication by minus one are summed to obtain the strategic inertia index (${\mathrm{strategic}}_{\mathrm{i},\mathrm{t}}$) of each enterprise in each year [43].

3.6. Control Variable

To minimize the impact of irrelevant factors on the overall modeling calculation, several variables were selected for control to ensure the smooth progress of the modeling study, thus putting all firms under equal conditions. Among them, the year variable, as a control factor, enables the comparison of these firms in the same measurement year, which is conducive to horizontal and vertical comparisons among firms. The other control variables are shown in

Table 1. Definition of variables and description of their values.

Variables	Symbol	Mean	S.D.	Sources
Dependent Variable
Corporate greenwashing—difference between standardized environmental, social, and governance disclosure scores and environmental, social, and governance performance scores	gw	−0.038	1.190	Wind Database CSMAR Database
Independent Variable
Public engagement—number of proposals by NPC deputies and CPPCC members	x	6.302	0.852	China Environmental Yearbook
Intermediary Variable
Environmental regulation—ratio of environmental terms in the Government’s annual working report to the total number of terms in the working report	gov			China Environmental Yearbook
Moderator Variable
Organizational inertia—The extent to which the organization’s strategic resourcing fluctuates over annual time frames	str	0.127	0.752	CSMAR Database
Control Variable
Year—dummy variable	age	2.815	0.348	CSMAR Database Wind Database
Enterprise size—natural logarithm of the total assets of the enterprise at the end of the period	size	23.083	1.288
Cash flows—ratio of net profit to total assets	cf	0.058	0.067
Liability—Total debt to total assets	debt	0.467	0.195
Tobin Q—Market value divided by the replacement cost of its assets	tobin	2.017	1.320
SOE dummy = 1 if the firm is state-owned and 0 if not	SOE

.

3.7. Model Design

Table 1 summarizes our variables. These variables were used to test the hypotheses we previously proposed. Specifically, we modeled the following:

Model (1): To test the impact of public participation on corporate greenwashing, the following model is constructed:

$${\mathrm{gw}}_{\mathrm{i},\mathrm{t}}=\mathsf{\alpha }+{\mathsf{\beta }\mathrm{lnx}}_{\mathrm{i},\mathrm{t}}+{\mathsf{\gamma }\mathrm{Control}}_{\mathrm{i},\mathrm{t}}+\mathrm{YearF}.\mathrm{E}.+\mathrm{FirmF}.\mathrm{E}.+{\mathsf{\epsilon }}_{\mathrm{i},\mathrm{t}}$$

(1)

where $\alpha$ is the model constant, $\beta ,\gamma$ is the coefficient of the variable, and ${\mathsf{\epsilon }}_{\mathrm{i},\mathrm{t}}$ is the value of data deviation.

Model (2): To test the moderating effect of organizational inertia on the relationship between public participation and corporate greenwashing, Model (2) is constructed as follows:

$$\begin{array}{c}{\mathrm{gw}}_{\mathrm{i},\mathrm{t}}=\mathsf{\alpha }+{\mathsf{\beta }}_1{\mathrm{lnx}}_{\mathrm{i},\mathrm{t}}+{\mathsf{\beta }}_2{\mathrm{str}}_{\mathrm{i},\mathrm{t}}+{\mathsf{\beta }}_3{\mathrm{lnx}}_{\mathrm{i},\mathrm{t}}{\ast \mathrm{str}}_{\mathrm{i},\mathrm{t}}+{\mathsf{\gamma }\mathrm{Control}}_{\mathrm{i},\mathrm{t}}\\ +\mathrm{YearF}.\mathrm{E}.+\mathrm{FirmF}.\mathrm{E}.+{\mathsf{\epsilon }}_{\mathrm{i},\mathrm{t}}\end{array}$$

(2)

where $\alpha$ is the model constant, ${\beta }_1, {\beta }_2, {\beta }_3, \gamma$ is the variable coefficient, and ${\epsilon }_{i,t}$ is the data deviation value.

Model (3): To test the effect of public participation on environmental regulation, Model (3) is constructed as follows:

$${\mathrm{lngov}}_{\mathrm{i},\mathrm{t}}=\mathsf{\alpha }+{\mathsf{\beta }\mathrm{lnx}}_{\mathrm{i},\mathrm{t}}+{\mathsf{\gamma }\mathrm{Control}}_{\mathrm{i},\mathrm{t}}+\mathrm{YearF}.\mathrm{E}.+\mathrm{FirmF}.\mathrm{E}.+{\mathsf{\epsilon }}_{\mathrm{i},\mathrm{t}}$$

(3)

where $\alpha$ is the model constant, $\beta ,\gamma$ is the coefficient of the variable, and ${\epsilon }_{i,t}$ is the data deviation value.

Model (4): To test the effect of environmental regulation on corporate greenwashing, Model (4) is constructed as follows:

$${\mathrm{gw}}_{\mathrm{i},\mathrm{t}}=\mathsf{\alpha }+{\mathsf{\beta }\mathrm{lngov}}_{\mathrm{i},\mathrm{t}}+{\mathsf{\gamma }\mathrm{Control}}_{\mathrm{i},\mathrm{t}}+\mathrm{YearF}.\mathrm{E}.+\mathrm{FirmF}.\mathrm{E}.+{\mathsf{\epsilon }}_{\mathrm{i},\mathrm{t}}$$

(4)

where $\alpha$ is the model constant, $\beta , \gamma$ is the variable coefficient, and ${\epsilon }_{i,t}$ is the data deviation.

Model (5): In order to test the mediating effect of environmental regulation, the environmental regulation variable is added to model (1) to construct the following Model (5):

$$\begin{array}{c}{\mathrm{gw}}_{\mathrm{i},\mathrm{t}}=\mathsf{\alpha }+{\mathsf{\beta }}_1{\mathrm{lnx}}_{\mathrm{i},\mathrm{t}}+{\mathsf{\beta }}_2{\mathrm{lngov}}_{\mathrm{i},\mathrm{t}}+{\mathsf{\gamma }\mathrm{Control}}_{\mathrm{i},\mathrm{t}}+\\ \mathrm{YearF}.\mathrm{E}.+\mathrm{FirmF}.\mathrm{E}.+{\mathsf{\epsilon }}_{\mathrm{i},\mathrm{t}} \end{array}$$

(5)

where $\alpha$ is the model constant, ${\beta }_1, {\beta }_2, \gamma$ is the coefficient of the variable, and ${\epsilon }_{i,t}$ is the deviation of the data value.

The above equation model is constructed based on the assumptions of H1, H2, and H3 mentioned earlier. Specifically, Model (1) is an analytical model based on H1. In this model, gw serves as the dependent variable, which is obtained by standardizing the variable data of corporate greenwashing. Here, “a” represents a constant. The other variables have already been clearly presented in the previous Table 1, so we won’t repeat them here. The hypothesis H1 can be further tested by examining the correlation between lnx and gw.

Model (2), in contrast, is constructed based on H3. In this model, “b” is the interaction term and “str” is the moderating variable. The strength of its moderating effect can be determined through data analysis.

The remaining three models are constructed based on the hypothesis of H2. They are used to test the relationships between public participation and environmental regulation, as well as between environmental regulation and corporate greenwashing, respectively, aiming to prove the corresponding hypotheses.

In the above models, the explanatory variable of $g{w}_{i,t}$ denotes the value of the corporate greenwashing indicator of enterprise i in year t, and the explanatory variable of $ln{x}_{i,t}$ denotes the standardized public participation indicator of enterprise i in year t. The mediating and moderating variables of $lngo{v}_{i,t}$ and $st{r}_{i,t}$ are explained in the same way. Based on the previous analysis, it can be seen that a observed coefficient $\beta$ that is significantly positive or significantly negative can be used to further determine the impact of public participation on corporate greenwashing, the mediating effect of environmental regulation, and the moderating effect that organizational inertia has.

Referring to the analytical approach of Zhang (2023) [47], this paper, after comprehensive consideration, adds variables, such as age, debt, size, cf, and tobin, to the above model to control for firm-level influences and to control for the fixed effects of year and firm.

3.8. Descriptive and Correlation Analysis

The means, standard deviations, and correlations of the variables are presented in

Table 2. Descriptive statistics and correlation analysis of variables.

	Mean	sd	$\mathbf{g}{\mathbf{w}}_{\mathbf{i},\mathbf{t}}$	$\mathbf{l}\mathbf{n}{\mathbf{x}}_{\mathbf{i},\mathbf{t}}$	$\mathbf{s}\mathbf{t}{\mathbf{r}}_{\mathbf{i},\mathbf{t}}$	age	size	cf	debt
${\mathrm{gw}}_{\mathrm{i},\mathrm{t}}$	−0.038	1.190	1
${\mathrm{lnx}}_{\mathrm{i},\mathrm{t}}$	6.302	0.852	−0.072 ***	1
${\mathrm{str}}_{\mathrm{i},\mathrm{t}}$	0.127	0.752	0.098 ***	−0.002	1
age	2.815	0.348	0.040 ***	−0.017	−0.019	1
size	23.083	1.288	0.183 ***	−0.130 ***	0.028 **	0.141 ***	1
cf	0.058	0.067	0.007	0.082 ***	0.058 ***	0.025 *	−0.019	1
debt	0.467	0.195	0.147 ***	−0.059 ***	−0.038 ***	0.126 ***	0.537 ***	−0.246 ***	1
tobin	2.017	1.320	−0.068 ***	0.053 ***	0.086 ***	−0.087 ***	−0.455 ***	0.224 ***	−0.438 ***

*, ** and *** denote p < 0.1, p < 0.05, p < 0.01, respectively, and p denotes probability.

. The maximum value of corporate greenwashing is 3.945, and the minimum value is −2.871, which indicates that the corporate greenwashing situations of different companies vary greatly. The weak correlation between the variables provides potential for further data processing.

4. Main Results

4.1. Baseline Regression Results

The results of the baseline regression are presented in

Table 3. Baseline regression analysis.

Variable Name	(1)	(2)
	$\mathbf{g}{\mathbf{w}}_{\mathbf{i},\mathbf{t}}$	$\mathbf{g}{\mathbf{w}}_{\mathbf{i},\mathbf{t}}$
${\mathrm{lnx}}_{\mathrm{i},\mathrm{t}}$	−0.095 ***	−0.067 ***
	(0.02)	(0.02)
age		0.204 ***
		(0.05)
size		0.160 ***
		(0.02)
cf		0.182
		(0.23)
debt		0.465 ***
		(0.10)
tobin		0.036 ***
		(0.01)
Year-fixed Effect	YES	YES
Firm-fixed Effect	YES	YES
N	6286	6286
Adj. R2	0.061	0.099

*** denotes p < 0.01, respectively, and p denotes probability.

. Column (1) of Table 3 controls only for time-fixed effects and firm-fixed effects, while column (2) further introduces relevant control variables. According to the displayed analysis results, the level of public participation is significant at the 1% level, indicating a significant negative correlation between public participation and corporate greenwashing. This suggests that as the level of public participation increases, the degree of corporate greenwashing decreases, supporting research hypothesis H1.

4.2. Robustness and Endogeneity Test

To ensure the robustness of the regression analysis results and verify that the findings are not driven by the measurement method of the data, we conducted a robustness analysis by altering the measurement of corporate greenwashing, following the approach of Zhang (2023) [48]. The results of this analysis are presented as follows in

Table 4. Robustness tests—greenwashing with variable replacement.

	(1)	(2)	(3)
	$\mathit{d}\mathit{i}{\mathit{s}}_{\mathit{i},\mathit{t}}$	$\mathit{d}\mathit{i}{\mathit{s}}_{\mathit{i},\mathit{t}}$	$\mathit{d}\mathit{i}{\mathit{s}}_{\mathit{i},\mathit{t}}$
${\mathrm{lnx}}_{\mathrm{i},\mathrm{t}}$	−0.042 ***	−0.172 ***	−0.103 ***
	(−3.17)	(−2.34)	(−1.22)
age		0.071 **	0.104
		(2.26)	(3.25)
size		0.292 ***	0.328 ***
		(29.39)	(28.42)
cf			0.303 *
			(3.51)
debt			−0.422 ***
			(−6.55)
tobin			0.009
			(1.45)
Year-fixed Effect	YES	YES	YES
Firm-fixed Effect	YES	YES	YES
N	6286	6286	6286
Adj. R2	0.03	0.17	0.18

*, ** and *** denote p < 0.1, p < 0.05, p < 0.01, respectively, and p denotes probability.

.

In this analysis, we adopt the research methodology proposed by Dongyang Zhang [47]. The purpose is to use ESG disclosure information as a proxy for corporate greenwashing data, with the degree of greenwashing measured by the ESG rating score. As shown in columns (1), (2), and (3), there is a significant negative correlation between public participation and ESG scores at the 1% significance level, indicating a strong correlation between these two variables. These results reinforce the robustness of the previous regression analysis.

Additionally, following the methodology of Niu et al. (2023) [53], this study further tests the robustness of the results by incorporating additional dimensions of fixed effects and adjusting the sample interval. We also distinguish between different attributes of enterprise qualities (state vs. non-state, high vs. low pollution). The results, presented in the first column of

Table 5. Robustness and endogeneity test.

	FEM	Sample Interval		${\mathbf{gw}}_{\mathbf{i},\mathbf{t}}$(M4)	${\mathbf{gw}}_{\mathbf{i},\mathbf{t}}$(M5)	${\mathbf{gw}}_{\mathbf{i},\mathbf{t}}$(M6)	${\mathbf{gw}}_{\mathbf{i},\mathbf{t}}$(M7)	Endogeneity
		2010–2014	2015–2019
	${\mathbf{gw}}_{\mathbf{i},\mathbf{t}}$(M1)	${\mathbf{gw}}_{\mathbf{i},\mathbf{t}}$(M2)	${\mathbf{gw}}_{\mathbf{i},\mathbf{t}}$(M3)	SOE	Non-SOE	High- Polluting	Low- Polluting	${\mathbf{gw}}_{\mathbf{i},\mathbf{t}}$(M8)
${\mathrm{lnx}}_{\mathrm{i},\mathrm{t}}$	−0.033 ***	−0.075 ***	−0.117 ***	−0.102	0.097 ***	0.204 ***	0.183 ***
	(−1.44)	(−2.01)	(−4.36)	(−2.12)	(4.15)	(5.01)	(3.71)
L.χi,								0.016 **
								(−2.27)
age	0.021	0.081	0.130	0.071	0.181	0.112	0.531 ***	0.662
	(0.18)	(0.01)	(0.11)	(0.54)	(0.65)	(2.21)	(4.34)	(2.49)
size	0.037	0.197 ***	0.256 ***	0.311	0.532 ***	0.391 ***	0.228 ***	0.543
	(0.12)	(3.31)	(1.83)	(0.12)	(0.77)	(4.06)	(1.16)	(2.04)
cf	0.316	0.040	0.388	0.052 ***	0.421	0.432 ***	0.229	0.074
	(1.43)	(1.22)	(0.79)	(3.01)	(0.91)	(3.01)	(0.123)	(3.95)
debt	−0.331	0.499 ***	0.542	0.034	0.743	0.874	0.396 ***	0.483 ***
	(−2.91)	(3.31)	(0.92)	(0.19)	(0.12)	(0.11)	(4.31)	(2.15)
tobin	0.004	0.001	1.021 ***	0.453 ***	0.049	0.632	2.83 ***	0.191 ***
	(0.97)	(0.55)	(3.49)	(2.48)	(0.44)	(0.52)	(0.98)	(4.87)
Year-fixed Effect	YES	YES	YES	YES	YES	YES	YES	YES
Firm-fixed Effect	YES	YES	YES	YES	YES	YES	YES	YES
Industry-fixed Effect	YES	NO	NO	YES	YES	YES	YES	YES
City-fixed Effect	YES	YES	NO	YES	YES	YES	YES	YES
N	6286	2718	3569	3211	3075	4001	2285	4576
Adj. R2	0.06	0.21	0.43	0.02	0.12	0.04	0.21	0.33

** and *** denote p < 0.05 and p < 0.01, respectively, and p denotes probability.

, demonstrate that the inclusion of multidimensional fixed effects does not lead to substantial changes, and the hypothesis remains valid. The results from the sample interval variation tests, shown in the second and third columns of Table 5, also reveal a significant negative correlation between public participation and corporate greenwashing. This indicates that the hypothesis continues to hold under different model specifications and sample adjustments.

In order to address the issue of endogeneity in the model, this study uses a lagged model with a one-period lag of public participation (L.χi,t) as an explanatory variable to support the hypotheses once again. The regression results, presented in column M4 of Table 5, show that the coefficient of L.χi,t is significantly positive at the 5% level. This indicates that, after mitigating the common endogeneity problem of reverse causality, the results remain robust.

4.3. Mediation Effect Test

The results of the baseline regression support the inhibitory effect of public participation on corporate greenwashing behavior.

Table 6. Mediation effect regression test.

	(1)	(2)
	$\mathbf{l}\mathbf{n}\mathbf{g}\mathbf{o}{\mathbf{v}}_{\mathbf{i},\mathbf{t}}$	$\mathbf{g}{\mathbf{w}}_{\mathbf{i},\mathbf{t}}$
$\mathrm{l}\mathrm{n}{\mathrm{x}}_{\mathrm{i},\mathrm{t}}$	0.091 ***	−0.050 ***
	(−16.61)	(−2.88)
age	−0.048 ***	0.169 ***
	(−3.25)	(3.81)
size	0.006	0.150 ***
	(1.29)	(9.80)
cf	0.048	0.054
	(0.65)	(0.25)
debt	−0.076 **	0.487 ***
	(−2.49)	(5.27)
tobin	−0.006	0.036 ***
	(−1.58)	(3.12)
$\mathrm{l}\mathrm{n}\mathrm{g}\mathrm{o}{\mathrm{v}}_{\mathrm{i},\mathrm{t}}$		−0.023 ***
		(2.67)
N	6286	6286
Adj. R2	0.09	0.09

** and *** denote p < 0.05 and p < 0.01, respectively, and p denotes probability.

presents the results of the mediation effects analysis, which tests the role of environmental regulation between public participation and corporate greenwashing.

Column (1) shows the regression analysis of the relationship between public participation and environmental regulation, controlling for other variables. The results indicate a coefficient of 0.091 (p < 0.01), suggesting a significant positive correlation—meaning that higher levels of public participation are associated with stronger environmental regulatory capacity. Column (2) illustrates the impact of environmental regulation on corporate greenwashing. The regression results show a coefficient of −0.023 (p < 0.01), indicating a significant negative effect. This suggests that as the intensity of environmental regulation increases, the degree of corporate greenwashing decreases. In conclusion, the data in Table 6 support the idea that public participation can curb corporate greenwashing behavior by strengthening environmental regulation, thus validating H2.

In addition, according to Table 6, the effect of public participation in reducing greenwashing behaviour directly is −0.050, while the effect of indirectly influencing greenwashing behaviour through environmental regulation is −0.0021. As a result, the overall negative effect of public participation on greenwashing behaviour is −0.0521, with the indirect effect accounting for 4.02% of the total effect. This suggests that the influence of public participation on corporate greenwashing behaviour comes mainly from the direct effect, but the indirect effect also contributes through the mediating path.

4.4. Moderating Effect Test

The moderating effect of organizational inertia on the relationship between public participation and corporate greenwashing is presented in

Table 7. Moderating effect regression test.

	(1)	(2)
	$\mathbf{g}{\mathbf{w}}_{\mathbf{i},\mathbf{t}}$	$\mathbf{g}{\mathbf{w}}_{\mathbf{i},\mathbf{t}}$
${\mathrm{lnx}}_{\mathrm{i},\mathrm{t}}$	−0.094 ***	−0.066 ***
	(0.02)	(0.02)
${\mathrm{str}}_{\mathrm{i},\mathrm{t}}$	0.104	0.123 ***
	(0.03)	(0.04)
${\mathrm{lnx}}_{\mathrm{i},\mathrm{t}}{\ast \mathrm{str}}_{\mathrm{i},\mathrm{t}}$	−0.075 ***	−0.061 ***
	(0.02)	(0.02)
age		0.207
		(0.05)
size		0.155
		(0.02)
cf		0.203
		(0.23)
debt		0.489 ***
		(0.11)
tobin		0.032 **
		(0.13)
Year-fixed Effect	YES	YES
Firm-fixed Effect	YES	YES
N	6286	6286
Adj. R2	0.067	0.105

** and *** denote p < 0.05 and p < 0.01, respectively, and p denotes probability.

. An analysis of columns (1) and (2) reveals that, after controlling for both time- and firm-fixed effects, the interaction term between public participation and organizational inertia, as well as the organizational inertia variable itself, are significant at the 1% level. This is true whether or not the control variables are included.

These results indicate that organizational inertia exerts a significant negative moderating effect, meaning that the greater the organizational inertia of a firm, the weaker the negative influence of public participation on corporate greenwashing. Figure 2 shows that the greater the organizational inertia of a firm, the weaker the negative impact of public participation on corporate greenwashing. This further supports the prediction of H3.

5. Conclusions and Implications

5.1. Conclusions

In the pursuit of green development, public participation plays an increasingly critical role in curbing corporate greenwashing behavior. However, how public participation affects corporate greenwashing behavior by influencing the external institutional environment is still an important issue that needs to be explored in depth. This study empirically examines the relationship between public participation, corporate greenwashing behavior, and organizational inertia using a sample of A-share listed companies in Shanghai and Shenzhen from 2010 to 2019. Through theoretical analysis and empirical research, the following main conclusions are drawn.

Public participation helps to inhibit corporate greenwashing behavior. This conclusion still holds even after a series of robustness tests, including variable substitution, model adjustment, sample interval change, and the use of a lagged model to deal with the endogeneity problem. Further research finds that public participation reduces greenwashing by strengthening environmental regulations. The proposals of the National People’s Congress (NPC) help to improve the environmental governance system, which in turn strengthens the regulation of corporate activities, and this regulatory environment encourages corporations to increase the transparency of environmental information disclosure.

Organizational inertia has a moderating effect on the relationship between public participation and corporate greenwashing. Firms with higher organizational inertia are more likely to adopt greenwashing strategies in the face of public pressure because inertia weakens the monitoring effect of public participation. These findings highlight the influence of public participation on firms’ greenwashing behavior and the moderating role of organizational inertia in firms’ decision-making, and provide new perspectives for related research, which can help to better understand the mechanism of how organizational inertia undermines the influence of public participation on firms’ greenwashing behavior and, thus, provide new insights for intervening in this type of business decision-making. This study provides new perspectives for related research and helps to understand how organizational inertia weakens the influence of public participation on corporate greenwashing behavior, thus providing new ideas for intervening in such behavior. For example, the use of modern information technologies, such as big data and blockchain, can significantly improve the transparency of corporate environmental information, enhance market and societal trust, and reduce the impediments to information flow caused by organizational inertia by providing real-time monitoring, establishing tamper-proof data storage, enabling transparent transaction records, performing automated smart contract execution, and enhancing data traceability. The public can more easily access real information on the environmental performance of enterprises and, thus, better participate in monitoring. In addition, enterprises can increase the number of discussions, seminars, and other activities with the public to promote communication and understanding between both sides. This will help to break the closure of enterprises due to organizational inertia and increase public participation.

5.2. Theoretical Significance

This study is of significance at the theoretical level. To our knowledge, it is the first time that public participation, organizational inertia, and corporate greenwashing behavior have been included in the same research framework, and the internal relationship between the three is systematically analyzed, which fills the research gap in this field. The study analyzes the specific paths through which public participation influences corporate greenwashing behavior and reveals the mechanism by which public participation inhibits corporate greenwashing by strengthening environmental regulations, providing a new theoretical basis for the understanding of corporate environmental behavioral decision-making. The exploration of the regulatory role of organizational inertia enriches the field of corporate environmental management, expands our understanding of the decision-making process of enterprises in the face of external pressures, and provides new perspectives for the cross-study of corporate strategic management theory and environmental management.

5.3. Practical Significance

From the enterprise level, this study provides crucial practical guidance for the sustainable development of enterprises. Firstly, enterprises need to fully recognize the significant impact of public participation on their development. Public participation reflects society’s expectations of corporate responsibility, so enterprises should regard it as a key signal. Subsequently, they should proactively integrate social and environmental responsibilities into their corporate strategic planning. When enterprises actively respond to the public’s environmental concerns, they can enjoy several benefits. On the one hand, it helps them build excellent public relations, enabling them to establish good interactions and trust with the public. On the other hand, the social capital of enterprises will increase, broadening their channels to obtain external support. Moreover, their social recognition and reputation will be significantly enhanced, making them more credible and influential in the market. However, enterprises should also be alert to the potential obstacles caused by organizational inertia. Although past experiences and established practices have supported business development to some extent, inertia may become a hindrance when it comes to the realization of green transformation, slowing down or even impeding the transformation process. Facing such a situation, enterprises should focus on cultivating a learning and adaptive culture. In this cultural atmosphere, employees will be more enthusiastic and capable of exploring and accepting new things. Meanwhile, when managing strategic changes, enterprises should adopt a flexible and wise attitude, not sticking to the old models but adjusting in a timely manner according to market and environmental dynamics. They should also actively promote organizational innovation to break free from the shackles of inertia. Ultimately, if enterprises successfully transfer to a sustainable development model and integrate green production practices into their core business processes, they can effectively reduce the occurrence of greenwashing behavior, steadily achieve long-term and sound development, and stand firm in the highly competitive business wave, meeting social and environmental requirements.

For policymakers, this study provides a decision-making reference for the formulation of effective environmental policies. Encouraging public participation in environmental governance is an important measure to promote the implementation of corporate environmental responsibility, but policymakers need to fully recognize the heterogeneity of corporate management. While enhancing public awareness of environmental protection and broadening participation channels to promote public participation in environmental governance, it should be noted that the inhibitory effect of public participation on corporate greenwashing is mainly realized through environmental regulation, which often requires the investment of a large amount of governance resources and may be lagged due to the cumbersome process of policy formulation [54]. In order to maximize the effectiveness of public participation, policymakers should actively explore other monitoring channels outside the formal system to improve monitoring efficiency. In addition, when formulating policies, it is necessary to fully consider the differences in organizational inertia of enterprises and provide more precise support and guidance to enterprises with high inertia and difficulties in strategic transformation, so as to help them successfully realize green transformation and avoid falling into the predicament of corporate greenwashing.

5.4. Innovation Point

The unique contributions of this study include the following: (1) difference in research focus: This study focuses on how public participation affects corporate greenwashing behaviour, emphasizing the multidimensional construction of the variable “public participation” and its mechanism analysis, rather than policy variables or consumer preferences. (2) Innovation in the theoretical framework: Based on social responsibility theory and stakeholder theory, this study proposes an integrated analytical framework to systematically explore the dynamic relationship between public participation and greenwashing.

5.5. Research Limitations

There are some limitations to this study. First, the analysis focuses on listed companies in China, which may bias the analysis of corporate behaviour on a global scale. Second, the reliance on secondary data may introduce sample selection bias. Furthermore, although environmental regulation was shown to be a key tool for public participation to reduce greenwashing, future research could explore other informal mechanisms through which public participation affects business conduct, e.g., through online media, social media platforms, word of mouth within companies, and informal groups of workers, to enrich the research model. We also hope that through this multi-faceted and diversified exploration, the relationship between these two variables will become clearer and more explicit in different cultural and regional contexts. This will help to develop more targeted corporate greenwashing management strategies on a global scale.

Moreover, after various considerations, we chose to mitigate the endogeneity problem with a lagged model. However, certain measures, like the instrumental variable method and the double difference method, were not adopted. The reason for this is that we found it more difficult to find valid instrumental variables that are strongly correlated but unrelated to the explanatory variables, due to the limitations of the data characteristics and the variable selection during the treatment process. Future studies can try to further explore this issue.

It is worth noting that while it is possible that some companies actively promote environmental protection in their corporate culture building to the extent that their environmental data may be free of corporate greenwashing, this study did not conduct targeted analysis due to a preliminary assessment of its low probability of occurrence for the time being. Subsequent studies will explore this key area in depth and, through more systematic research and analysis, will comprehensively assess the authenticity and effectiveness of environmental initiatives to ensure the completeness and rigor of the study.

Finally, the imperfect ESG disclosure mechanism, unstable disclosure quality, lack of systematic research on ESG assessment and rating, and weak database construction, coupled with the weak influence of ESG investment and insufficient development of green investors, together constitute the main challenges of current ESG practice. Addressing these issues requires global standardization, more in-depth academic research, and the active participation of green investors. In our study, we used ESG scores as part of our measure of corporate greenwashing. Future researchers should refine this approach by focusing on the environmental element (removing social and governance elements). In addition, they should compare our approach to other methods of assessing greenwashing to further validate our measure.

Overall, this research offers valuable insights into the relationship between public participation, corporate greenwashing, and organizational inertia. However, it also highlights the need for further exploration and refinement in both research methods and practical applications to better address the complex challenges in the field of corporate environmental behavior and sustainability.