Foreign Residency Rights and Corporate Greenwashing: Evidence from China’s Heavily Polluting Industries

Abstract

Against the backdrop of economic globalization and the increasing adoption of ESG principles, the phenomenon of Chinese private firms’ actual controllers obtaining foreign residency rights has garnered societal attention. Among the emerging issues, “whether and how actual controllers’ foreign residency rights influence corporate greenwashing behavior” has become a critical theoretical and practical concern. This study examines Chinese privately listed A-share companies in heavily polluting industries from 2010 to 2021, employing text analysis to identify symbolic and substantive environmental behaviors through the lens of environmental information disclosure, thereby constructing a comprehensive greenwashing measurement index system. The findings reveal a significant positive correlation between actual controllers’ foreign residency rights and corporate greenwashing, with this effect demonstrating long-term persistence. Heterogeneity analysis indicates that this relationship is more pronounced in companies where actual controllers exercise direct control compared to those with indirect control. Further tests demonstrate that enhanced internal control quality, increased media scrutiny, and stringent audit supervision can effectively mitigate the greenwashing-promoting effect of actual controllers’ foreign residency rights. The conclusions not only extend the theoretical framework of how executive characteristics influence corporate decision-making but also provide a reference governmental departments can use to improve the environmental regulatory policies of affiliates of holders of overseas residency rights.

1. Introduction

With increasing public awareness of ecological and environmental protection, companies in heavily polluting industries and their environmental responsibility have been attracting increasing attention. The environmental information disclosed in corporate social responsibility (CSR) reports serves as a crucial reflection of a company’s environmental commitments. However, some companies employ impression management tactics or selectively disclose environmental information in their CSR reports to mislead stakeholders. These corporate greenwashing practices pose significant obstacles to sustainable development [1]. For instance, such greenwashing behaviors severely undermine market competition fairness, misguide consumer decision-making, erode public trust, and substantially impede the dissemination of green development principles as well as the advancement of sustainability strategies. Corporate environmental disclosures contain substantial qualitative textual information with strong professional characteristics, making greenwashing difficult to effectively define and identify while also posing challenges for data acquisition. As a form of pseudo-CSR behavior, greenwashing represents a preferred opportunistic strategy that can generate short-term benefits for companies [2]. Previous research has found that companies with characteristics such as high growth potential [3], high organizational visibility [4,5], and a high degree of digital transformation [6] are more likely to engage in greenwashing. From the perspective of corporate decision-makers, narrow decision frameworks and optimism bias represent individual-level motivations for greenwashing behavior [7]. Organizational and individual psychological characteristics, along with agent-bounded rationality, help explain greenwashing practices [8]. For example, Abdullah et al. [9] demonstrate that firms led by narcissistic CEOs are more likely to engage in greenwashing. Certainly, managers’ preferences and decisions about environmental strategies directly influence the level and quality of corporate environmental disclosures. For example, as highlighted by Hao et al. [10], executives’ green cognition mitigates corporate greenwashing behavior, which, in turn, elevates the transparency and comprehensiveness of environmental disclosures.

Prior research has established that the personal characteristics of actual controllers influence corporate management activities [11], with the possession of foreign residency rights emerging as a particularly consequential attribute. Studies have found that actual controllers with foreign residency rights lead to higher probabilities of corporate fraud [12], increased audit fees [13], reduced access to external financing [14], and higher stock price crash risk [15]. However, while these studies have primarily examined the financial implications of actual controllers’ foreign residency rights, there remains a notable research gap regarding how this characteristic affects corporate environmental behaviors, particularly greenwashing practices. Drawing on the private benefits of control theory, we posit that when actual controllers of private companies obtain foreign residency rights, which provide them with greater mobility and border-crossing convenience, they may be incentivized to pursue personal benefits at the potential expense of genuine environmental commitments. Chen et al. [12] demonstrated that when firms face bankruptcy or crises, wealthy individuals can use their foreign residency rights to flee abroad, significantly increasing the difficulty for regulatory authorities to track and supervise them; these individuals’ foreign residency rights thus allow them to evade legal sanctions. For actual private enterprise controllers, foreign residency rights provide an escape route to avoid responsibility when their greenwashing behaviors lead to severe consequences. This raises a crucial research question: does the possession of foreign residency rights by actual controllers in private firms prompt companies to engage in more greenwashing behaviors?

This study focuses on examining the economic consequences of actual controllers’ foreign residency rights for firms’ greenwashing behaviors. This study examines private companies listed on the China A-share list in heavily polluting industries between 2010 and 2021. Using textual analysis methods, we identify symbolic and substantive environmental behaviors from the perspective of environmental information disclosure and construct a greenwashing measurement index system. Based on this framework, we investigate the relationship between the foreign residency rights of actual controllers and corporate greenwashing behavior. We find that, first, the foreign residency rights of the actual controllers in heavily polluting private companies lead to increased corporate greenwashing behavior, and this facilitating effect is more pronounced when the actual controllers directly control the listed company. Second, both internal control mechanisms and external media supervision can effectively mitigate the impact of actual controllers’ foreign residency rights on corporate greenwashing. Third, adequately increasing audit fees can also significantly restrict the influence of actual controllers’ foreign residency rights on corporate greenwashing. Fourth, the impact of actual controllers’ foreign residency rights on corporate greenwashing behavior persists over the long term.

The contributions of this study are threefold. First, we incorporate the foreign residency rights of actual controllers in listed private firms into the analytical framework of corporate greenwashing determinants. Second, we develop a greenwashing measurement system that employs textual analysis to distinguish between symbolic and substantive environmental behaviors in corporate disclosures. Third, we examine both internal and external governance mechanisms for greenwashing regulation, proposing practical solutions for its mitigation.

The subsequent structure of this paper is as follows: Section 2 presents the literature review and research hypotheses, Section 3 explores the data and methods, Section 4 presents empirical testing and analysis, and Section 5 provides the conclusion.

2. Hypothesis Development

According to the private benefits of control theory, actual controllers exert decisive influence over corporate strategy formulation by dominating board decisions and directing critical corporate actions [16]. In particular, compared to SOEs, the actual controller in private firms usually has more discursive power and can exercise extensive control over the firm based on their influence, while their foreign residency rights also affect their decision-making behavior, thus influencing the firm’s greenwashing behavior. Wang et al. [17] point out that when the actual controller has the right to a ‘fallback’ in foreign residency, the conflict of interest between the actual controller and creditors can be aggravated. Foreign residency rights of actual controllers induce corporate myopia by diverting firms from long-term objectives and reducing investments in CSR initiatives and innovation activities [18]. Concurrently, such rights exacerbate financing constraints, leading to diminished R&D expenditures and human capital investments [19]. The short-term self-interest orientation inherent to actual controllers’ conflicts fundamentally with sustainable firm development. Therefore, even if the greenwashing behavior will cause serious harm to the firm in the future, the actual controller can use their foreign residency rights as a special status to get out of the situation, so the foreign residency rights of the actual controller can affect the greenwashing behavior of the firm.

Corporate social responsibility generally includes pollution control, sustainable development, public utility construction, employee welfare, etc., and the fulfillment of these responsibilities invariably requires large expenses; these lead to an increase in the operating costs of firms, contradicting the goal of maximizing the benefits pursued by firms [20]. In circumstances where there is information asymmetry and the environmental information disclosure system needs to be further improved, most of the consumer’s knowledge about the sustainability of firms comes from the social responsibility reports disclosed by the companies on their initiatives, as well as the environmental protection sections of the annual reports. Companies may adopt common impression management techniques, such as over-amplifying their problem-solving abilities, dramatically downplaying bad news, and concealing damaging information in their disclosures [21] to embellish environmental stewardship and project a misleadingly positive ecological image [22]. The practice of impression management in environmental disclosures within corporate social responsibility reports has become a prevalent strategy among many firms [23].

For heavily polluting industries, where regular environmental disclosure has gradually evolved into a mandatory requirement and environmental stewardship represents a key expectation from external stakeholders, the inherent conflict between the substantial costs and long-term nature of genuine environmental investments and actual controllers’ pursuit of private benefits of control creates significant tension. To preserve actual controllers’ private benefits while complying with environmental disclosure mandates, entities in environmentally sensitive industries strategically deploy symbolic environmental reporting tactics. CSR reports, serving as the primary vehicle for disclosing environmental performance in these industries, consequently become crucial platforms for such impression management. Prior research indicates that corporations may utilize CSR disclosures for impression management and greenwashing objectives [24,25]. Actual controllers play pivotal roles in mediating environmental performance outcomes based on risk preferences. As evidenced by Maqsood et al. [26], foreign residency rights among actual controllers negatively impact corporate green innovation. When greenwashing functions as an impression management tactic, actual controllers possessing foreign residency status face heightened incentives to engage in such practices within sustainability reports, simultaneously securing private benefits of control while projecting environmentally conscientious organizational imagery. It is within this context that actual controllers’ possession of foreign residency rights may create conditions conducive to increased greenwashing behaviors, as the mobility and reduced accountability associated with such status may amplify their propensity to prioritize impression management over substantive environmental actions. Based on the foregoing analysis, we posit the following hypothesis:

H1a. 

Ceteris paribus, the foreign residency rights of actual controllers have positive effects on corporate greenwashing.

Wu and Xu [27] posit that institutional contexts and operational environments jointly subject firms to multidimensional public pressures, which compel them to issue CSR reports with environmental disclosures as a responsive measure; however, this very process of impression management in CSR reporting may inadvertently lead to corporate greenwashing. Conversely, mounting public pressures may alternatively motivate firms to adopt genuine environmental practices and enhance their environmental disclosure quality [28], resulting in CSR reports that emphasize substantive environmental actions over symbolic gestures, thereby potentially mitigating greenwashing tendencies under the framework of public pressure theory.

From an internal governance perspective, the principal-agent mechanism serves as an institutional solution to the inherent separation of ownership and control and information asymmetry. When actual controllers exercise their prerogatives for private benefit extraction, robust internal governance structures can function as an effective counterbalance. High-quality internal control systems, as demonstrated by Li et al. [29], operate as critical monitoring mechanisms that constrain managerial opportunism, reduce agency costs, and incentivize decision-making aligned with long-term corporate interests, thereby elevating managerial attention to authentic environmental compliance rather than superficial greenwashing. Consequently, when facing public pressures for environmental transparency, firms with effective internal governance are more likely to respond substantively by improving genuine environmental performance and reducing greenwashing practices.

H1b. 

Ceteris paribus, the foreign residency rights of actual controllers have negative effects on corporate greenwashing.

3. Data and Methodology

3.1. Data and Sample Selection

We take A-share listed private companies involved in heavily polluting industries in Shanghai and Shenzhen in China that issued social responsibility reports during 2010–2021 as the research object, and the sample is selected for the following reasons. First, the Guidelines for the Disclosure of Environmental Information of Listed Companies (2010) determined the classification of high-pollution industry, and companies in high-pollution industry should disclose environmental information regularly. Second, after 2009, Southern Weekly published a greenwashing ranking for six consecutive years, and only after that did the government and the media begin to pay more attention to corporate greenwashing. Third, this study restricts its sample period to data preceding 2022 to mitigate anticipatory confounding effects, given that the establishment of the International Sustainability Standards Board (ISSB) by the IFRS Foundation on 3 November 2021, tasked with developing a global baseline for high-quality sustainability disclosures, prompted the release of the exposure draft IFRS S1 General Requirements for Disclosure of Sustainability-related Financial Information on 31 March 2022. Anticipating profound implications for ESG reporting standards, firms likely initiated strategic adjustments to their sustainability disclosure practices throughout 2022, engaging in preemptive adaptation of disclosure strategies that could fundamentally alter observed patterns of greenwashing behavior. By excluding observations generated post-2021, we isolate the relationship between actual controllers’ foreign residency rights and corporate greenwashing from firms’ forward-looking responses to these impending regulatory transformations. Fourth, foreign residency rights are involved only if the actual controller is a natural person and the actual controller of state-owned firms is not a natural person, so the research object of this paper is listed as private firms.

We screen the samples as follows: (1) excluding the samples that were ST and *ST during the sample period, because ST companies are more special and their disclosure of environmental information may be different from that of non-ST companies; (2) excluding the samples in which the companies do not have an actual controller; and (3) excluding the samples with missing data, ultimately obtaining 924 social responsibility reports from 199 companies. To exclude the influence of outliers and extreme values, we winsorize all continuous variables at the 1st and 99th percentiles. This study employs a meticulous manual data collection approach by systematically analyzing environmental disclosures extracted from corporate social responsibility reports and dedicated environmental sections within annual reports, supplemented by hand-collected data on actual controllers’ foreign residency rights obtained through direct examination of the “Basic Information on Controlling Shareholders and Actual Controllers” section in company annual reports. All CSR reports and annual reports were sourced from the official CNINFO disclosure platform, while financial characteristics data were acquired from the CSMAR database.

3.2. Variable Definitions

3.2.1. Foreign Residency Right

The independent variable is the foreign residency rights of an actual controller, denoted by ID. ID takes a value of 1 when the actual controller has a foreign nationality or foreign residency outside the country, and 0 otherwise. In addition, when there is more than one actual controller of a firm, the actual controller of the firm is considered to have foreign residency rights as long as one of them has foreign residency rights.

3.2.2. Corporate Greenwashing

The dependent variable is the level of greenwashing (GWL). Based on the characteristics of environmental information disclosure in CSR reports, we construct the corporate greenwashing indicator system from a total of twenty secondary indicators in four primary indicators, such as governance and institutions, external norms, internal evaluation, and green optimization, as shown in Table 1. The measurement procedure for each indicator involves four sequential steps: first, the content of corporate social responsibility reports is categorized according to the primary and secondary indicators specified in Table 1 using text analysis methodology; second, to ensure scoring objectivity, two independent experts initially evaluate each company’s classified textual data for every indicator, with formal scoring commencing only after achieving 90% inter-rater reliability, wherein any scoring discrepancies are reconciled by a third arbiter. For each indicator, ‘Yes’ is scored as 1, and ‘No’ is scored as 0; third, the scoring criteria are applied such that the statements of the relevant indicators in the governance and institutions and green optimization sections are substantive disclosures if they have low substitutability or are presented in the form of cases; otherwise, they are symbolic disclosures; the statements of the relevant indicators in the external norms and internal assessment sections are substantive disclosures if they are quantitative disclosures; otherwise, they are symbolic disclosures; fourth, upon completion of this standardized scoring process, the symbolic disclosure score and substantive disclosure score are separately calculated.

We define the manifestations of corporate greenwashing behavior as selective disclosure and representational manipulation, with selective disclosure meaning that firms selectively disclose their well-performing environmental matters in their social responsibility reports, and representational manipulation meaning that firms embellish their green image through the use of strategic representations in their social responsibility reports. We measure the degree of selective disclosure based on the number of items disclosed and the number of matters that firms should disclose, and the calculation formula is as follows:

Selective disclosure (Gwls) = 100 × (1 − number of items disclosed/number of matters to be disclosed).

The degree of representational manipulation is measured on the basis of the number of symbolic disclosures and the number of items disclosed, calculated using the following formula:

Representational manipulation (Gwle) = 100 × (number of symbolic disclosures/number of matters disclosed).

Finally, the geometric mean was used to calculate the greenwashing score (Score) for each firm:

(1)$\mathit{Score} = \sqrt{\mathit{Gwls} \times \mathit{Gwle}}$

We divided the greenwash score by 100 and used the percentage to measure company greenwashing (GWL):

GWL = Score/100(2)

The value of GWL ranges from 0 to 1. A higher value of GWL indicates a higher degree of corporate greenwashing, and vice versa.

3.3. Research Model

To examine the effect of the foreign residency rights of the actual controller on greenwashing practices in privately listed firms, we set the following regression model to test the hypothesis. A statistically significant positive coefficient α₁ in Equation (3) would provide empirical support for Hypothesis 1a.

(3)${\mathit{GWL}}_{i,t}={ \alpha }_0+{ \alpha }_1{\mathit{ID}}_{i,t}+{\sum }_{n=2}^{16}{\alpha }_n{\mathit{Controls}}_{i,t}+\mathit{Year}+\mathit{Industry}+{ \epsilon }_{i,t}$

In Equation (3), the dependent variable GWL_i,t is the firm’s greenwash score, the independent variable ID_i,t refers to whether or not the actual controller of the firm has the foreign residency right, and Controls_i,t is a series of factors that can affect the greenwashing behavior of the firm, including the size of a firm (Size), financial leverage (Lev), profitability (ROA), and growth (Growth), total asset turnover (Ato), cash flow ratio (Cashflow), fixed asset ratio (Fixed), sole director ratio (Indep), the shareholding ratio of the top 5 shareholders (Top5), checks and balances (Balance), book-to-market ratio (MB), listing age (Listage), redundant resources (Slack), and the location of the firms (Area₁ and Area₂). In addition, we further control for year-level and industry-level fixed effects. Table 2 shows the definitions of the variables.

4. Empirical Results

4.1. Descriptive Statistics

Table 3 presents descriptive statistics for the main variables. In Table 3, the variable greenwashing (GWL) has a minimum value of 0.075, a maximum value of 0.894, and a standard deviation of 0.194, indicating that there is high variation in the degree of greenwashing between the firms in the sample. The mean value of the variable foreign residency rights (ID) is 0.140, indicating that the number of firms in the sample whose actual controller has foreign residency rights is about 14%. The untabulated results show that the variance inflation factor of each variable is less than 10, and the mean variance inflation factor is 1.630, indicating that there is no multicollinearity problem. The correlation matrix is presented in Appendix A.

4.2. Main Results

We present the regression results of Equation (3) in Table 4. The results in column (1) show that the regression coefficient of ID without control variables is 0.053, which is significantly positive at the 1% level. After incorporating a series of control variables that can affect greenwashing practices of firms, the results in column (2) show that the regression coefficient of ID is 0.061, which is significantly positive at the 1% level, suggesting that the foreign residency rights of an actual controller drive firms to engage in more greenwashing behaviors than firms whose actual controller does not have foreign residency rights. This finding suggests that upon obtaining foreign residency rights, actual controllers in private firms pursue increased greenwashing practices to facilitate environmental impression management aimed at embellishing their firms’ ecological image while extracting private benefits of control, thereby empirically validating our research hypothesis H1a. Regarding the control variables, the vast majority exhibit statistical significance, confirming the appropriateness of their selection.

4.3. Robustness Tests

4.3.1. Alternative Variable Analysis

For the dependent variable, following the approach of Huang [30], we define corporate greenwashing (RGWL) as a binary variable (0 or 1) based on the median threshold (50th percentile). Specifically, firms with levels of greenwashing (GWL) that exceed the median are assigned RGWL = 1 and 0 otherwise. We then re-estimate the model using a logit regression with this discrete measure. Column (1) of Table 5 presents the results, showing that the coefficient of foreign residency rights of an actual controller (ID) is 1.062 and statistically significant at the 1% level. This confirms that the foreign residency rights of the actual controller continue to exacerbate corporate greenwashing even after altering the measurement approach. For the independent variable, we adopt the methodology of Luo [31] and construct the ratio of foreign residency rights (RID), calculated as the number of controllers holding foreign residency rights divided by the total number of controllers. As reported in column (2) of Table 5, the coefficient of RID remains significantly positive, further supporting our hypothesis.

4.3.2. Alternative Sample Analysis

We use three samples for the regressions to mitigate the interference that different samples may have on the findings. First, to avoid different impacts of multiple actual controllers on the greenwashing behavior of firms due to differences in opinions, we draw on Luo [31] and select firms with only one actual controller to rerun the regression, and the results are reported in column (3) of Table 5. Second, since China’s Guangdong and Fujian provinces historically have had more immigrants, this may have a greater impact on whether actual controllers of firms in the region acquire foreign residency rights, which, in turn, can interfere with the findings. To rule out this possible interference, we draw on the study of Wang [32] to exclude samples from listed firms whose domiciles are located in Guangdong Province or Fujian Province and rerun the regressions, and the results are reported in column (4) of Table 5. Third, since the samples of firms in the mining and chemical industry account for approximately two thirds of the samples of heavy polluters, we draw on the methodology of Huang et al. [33] and select the samples of firms in the mining and chemical industry categories in heavily polluting industries and repeat the regression; the results are reported in column (5) of Table 5. In columns (3) to (5) of Table 5, the regression coefficients of the actual controller’s foreign residency rights (ID) are significantly positive, 0.133, 0.051, and 0.099, respectively, indicating that the findings of our paper are robust.

4.3.3. Lag Identification

Although our baseline results demonstrate that actual controllers’ foreign residency rights positively affect corporate greenwashing practices, these findings may be subject to endogeneity concerns. There could be a potential bidirectional causality between foreign residency rights and greenwashing behaviors. While obtaining foreign residency rights may encourage actual controllers to engage in greenwashing, the occurrence of greenwashing could conversely motivate actual controllers to acquire foreign residency rights.

To address these endogeneity issues, we re-estimate Equation (3) using one-period-lagged values of both the dependent variable and control variables. As presented in column (6) of Table 5, the regression coefficient of ID remains statistically significant and positive, confirming the robustness of our main conclusions.

4.3.4. Heckman Two-Stage Estimation

To mitigate potential sample selection bias in our estimation, we implement Heckman two-stage estimation as a robustness test. In the first stage, we estimate the determinant of actual controllers’ foreign residency rights (ID) using a Probit model that incorporates all baseline control variables plus the wedge between cash flow rights and voting rights (i.e., the divergence between ownership and control). From this estimation, we derive the inverse Mills ratio (IMR). In the second stage, we re-estimate our primary specification (Equation (3)) while including the computed IMR as an additional regressor. As shown in column (7) of Table 5, the coefficient of IMR is 0.294 (significant at the 5% level), confirming the presence of sample selection bias that warrants correction. Importantly, the coefficient of ID remains positive and statistically significant, demonstrating that our main findings persist after considering potential selection effects.

4.3.5. Addressing Omitted Variable Concerns

The presence of political connections among corporate executives may alter governmental oversight intensity over greenwashing or environmental practices, rendering executive political affiliation a potentially significant factor influencing corporate greenwashing behaviors. Consequently, this study further controls for executives’ political connections in the regression model through re-estimation. The political connection variable (Political) is assigned a value of 1 if either the chairman of the board or the general manager currently holds or formerly held a government official position, and 0 otherwise. Regression results are presented in column (8) of Table 5, which demonstrates that after controlling for Political, the regression coefficient for ID remains statistically significant and positive at the 1% level. This confirms the persistent impact of private firms’ actual controllers’ foreign residency rights on corporate greenwashing even when accounting for executive political connections, thereby indicating the robustness of our primary conclusions.

4.4. Additional Analysis

4.4.1. The Impact of Actual Controllers’ Different Control Methods

Actual controllers exercise control through three primary methods: direct shareholding, pyramid structures, and cross-holdings [34]. Direct shareholding involves a single-layer control structure in which the actual controller possesses sufficient voting rights to exert direct control. Pyramid structures occur when the actual controller maintains a chain of ownership with at least one listed company while holding more than 20% of voting rights. Cross-holdings refer to situations in which actual controllers hold stakes in other controlled firms within the ownership chain.

Following the prior literature, we classify control methods into two categories: direct control (solely through direct shareholding) and indirect control (via pyramid structures or cross-holdings). When actual controllers exercise direct control, their characteristics and preferences can exert a more pronounced influence on corporate decision-making, potentially maximizing the private benefits of control. This suggests stronger motivations and a higher likelihood of engaging in greenwashing practices. On the contrary, indirect control methods introduce additional monitoring from internal and external governance factors, which can restrict the ability of actual controllers to influence corporate greenwashing behavior.

To examine how control methods moderate the relationship between foreign residency rights and corporate greenwashing, we partition our sample into direct control and indirect control subsamples. Columns (1) and (2) of Table 6 present the regression results for these subsamples, respectively. The coefficient of foreign residency rights (ID) is significantly positive in the direct control subsample (column 1), while statistically insignificant in the indirect control subsample (column 2). These results suggest that the greenwashing-enhancing effect of the foreign residency rights of actual controllers manifests itself primarily in firms with direct control structures.

4.4.2. Effects Across Different Heavily Polluting Sub-Industries

Given the heterogeneity within heavily polluting industries where the applicability of greenwashing may vary across sectors, the impact of actual controllers’ foreign residency rights on corporate greenwashing could differ among sub-industries. Accordingly, following the industry classification outlined in the “Environmental Information Disclosure Guidelines for Listed Companies” (2010), this study categorizes sub-industries based on the first-digit industry code (utilizing the first two digits for manufacturing sub-industries) and conducts regression analyses by sub-industry. The regression results in Columns (3) and (4) of Table 6 indicate that the positive effect of actual controllers’ foreign residency rights on corporate greenwashing is observed exclusively in polluting firms within the manufacturing sector with two-digit codes C1 and C2.

4.4.3. The Governance Effect of Internal Control

Corporate governance represents the most critical determinant of firm social responsibility performance [35]. As the institutional foundation of corporate governance mechanisms, high-quality internal control systems mitigate principal–agent conflicts, curb managerial opportunism, and provide institutional safeguards for the fulfillment of corporate social responsibility. Our analysis reveals two distinct yet complementary channels through which internal controls affect greenwashing behaviors.

First, robust internal controls establish an effective monitoring framework that restricts managerial discretion [29]. By reducing opportunistic behaviors that prioritize personal gains over organizational interests, these controls compel executives to make decisions based on a comprehensive analysis of operational conditions and long-term development strategies. This institutional pressure raises managerial attention to authentic environmental practices rather than symbolic greenwashing.

Second, China’s Basic Standards for Enterprise Internal Control explicitly incorporate environmental protection into operational requirements [36], transforming ecological compliance from voluntary practice to a mandatory control objective. Guo et al. [37] find that internal control can inhibit corporate greenwashing behaviors. Therefore, we further examine whether high-quality internal controls can mitigate the positive effect of actual controllers’ foreign residency rights on corporate greenwashing.

To empirically test this governance effect, we measure internal control quality (IC) using the DIB index of the internal control and risk management database, constructed based on the principles of the COSO framework. This comprehensive metric (theoretical range: 0–1000) is standardized by dividing by 100 to ensure dimensional consistency. As shown in column (5) of Table 5, the significantly negative coefficient of ID × IC confirms our hypothesis that effective internal controls mitigate the greenwashing-enhancing effect of the foreign residency rights of actual controllers. This finding indicates that for private firms whose actual controllers possess foreign residency rights, their greenwashing behaviors gradually decrease as the quality of internal control improves.

4.4.4. The Governance Effect of Media Supervision

Although China has not yet established specific legal policies targeting corporate greenwashing, companies often disclose environmental information as a strategic response to public pressure arising from media scrutiny. Yue and Li [38] and Sun et al. [39] demonstrate that media attention, as a form of external supervision, directly curbs corporate greenwashing practices. When greenwashing behavior is exposed by the media, actual controllers, despite the convenience of evading responsibility through foreign residency rights, may still reduce symbolic environmental actions or enhance substantive eco-friendly initiatives due to heightened public pressure. This external oversight forces companies to align with national environmental standards, thus mitigating opportunistic greenwashing behavior.

To examine the moderating role of media supervision, we follow Kong et al. [40] and construct a media attention measure (Media) based on the annual count of news reports covering each firm from eight leading financial newspapers and magazines (China Securities Journal, Shanghai Securities News, China Business News, 21st Century Business Herald, China Business Journal, The Economic Observer, Securities Daily, and Securities Times), sourced from the CNRDS database. This approach accounts for the reporting of timeliness, quality, social influence, and data availability. To mitigate scale effects, we take the natural logarithm of one plus the total coverage of the media (ln (1 + Media)).

Column (6) of Table 6 presents the regression results. The significantly negative coefficient of ID × Media confirms that media supervision effectively weakens the positive association between the foreign residency rights of actual controllers and corporate greenwashing. This result demonstrates that for private firms where actual controllers hold foreign residency rights, their greenwashing behaviors progressively diminish as external media coverage and scrutiny of the company increase.

4.4.5. Examining Audit Regulatory Influence

Huang [30] documents that greenwashing firms employ impression management tactics in sustainability reports to influence audit pricing. Based on this finding, we examine whether increased audit fees mitigate the positive effect of foreign residency rights of actual controllers on corporate greenwashing.

Using the natural logarithm of audit fees (Lnfee) to measure external audit regulations, we present the regression results in column (7) of Table 6. The coefficient of foreign residency rights (ID) remains significantly positive, while the interaction term ID × Lnfee shows a statistically negative coefficient at the 1% level. This suggests that higher audit fees effectively constrain the greenwashing-enhancing effect associated with foreign residency rights. This result demonstrates that for private firms whose actual controllers possess foreign residency rights, increases in audit fees correspond to progressively mitigated greenwashing behavior. The observed moderating effect may operate through a channel; that is, elevated audit fees reflect more rigorous monitoring and higher quality audits, reducing the ability of actual controllers to manipulate environmental disclosures.

4.4.6. Long-Term Effects of Actual Controllers’ Foreign Residency Rights on Corporate Greenwashing

To examine the persistence of the impact of foreign residency rights on greenwashing practices, we regress the current period residency status (ID) on the greenwashing behavior of firms over three subsequent years (t + 1 to t + 3). As presented in columns (8) to (10) of Table 6, the coefficients of ID remain statistically significant at the 1% level in all future periods. These results demonstrate that the greenwashing-enhancing effect of the foreign residency rights of actual controllers exhibits long-term persistence.

5. Conclusions

5.1. Research Conclusions

This study examines the impact of foreign residency rights of actual controllers on corporate greenwashing behavior among privately listed A-share companies in heavily polluting industries on China’s Shanghai and Shenzhen stock exchanges from 2010 to 2021. Our findings highlight that in heavily polluting industries, the foreign residency rights of actual controllers lead to increased corporate greenwashing behavior, and this effect persists over the long term. This impact is mainly observed in companies where actual controllers exercise direct control rather than indirect control. Both internal and external monitoring mechanisms, including high-quality internal controls, media supervision, and rigorous audit oversight, effectively mitigate the influence of the foreign residency rights of actual controllers on corporate greenwashing. Our study contributes to the literature by enriching our understanding of the drivers of corporate greenwashing behavior from the perspective of the foreign residency rights of actual controllers. The findings also provide valuable information to regulatory authorities to improve the standardization of corporate social responsibility reporting and improve the quality of environmental information disclosure.

5.2. Research Insights and Policy Recommendations

Regulatory authorities should enhance the quality of disclosure requirements pertaining to ultimate controllers’ overseas residency rights in private firms while strengthening oversight and punitive measures for environmental disclosure violations within heavily polluting industries. Disclosure protocols must explicitly mandate reporting on residency rights held by immediate family members as statutory related parties. Simultaneously, regulatory frameworks for corporate social responsibility reports and environmental disclosures should be refined to elevate standards, improve transparency, and heighten vigilance against greenwashing in environmentally sensitive sectors.

Listed companies must cultivate genuine environmental stewardship and continuously improve internal governance mechanisms. Robust governance structures are essential for effectively checking managerial behavior through intensified monitoring and incentive alignment. Governance bodies should promptly identify and sanction greenwashing practices upon detection. Internal oversight mechanisms must actively constrain managerial opportunism and rigorously supervise environmental decision-making to substantively deter symbolic rather than substantive environmental actions.

Consumers need to develop critical literacy for identifying greenwashing in CSR communications. Engaging with diverse information channels to evaluate corporate environmental performance will enhance discernment and enable objective assessments of firms’ ecological commitments. Where substantiated greenwashing occurs, consumers should strategically leverage media exposure to amplify public pressure, thereby motivating firms to improve both the quality and integrity of their environmental disclosures.

5.3. Limitations and Future Research Directions

While this study makes important theoretical and practical contributions by examining the relationship between actual controllers’ foreign residency rights and corporate greenwashing in heavily polluting privately listed companies, several limitations warrant acknowledgment and present opportunities for future research.

The current lack of standardized disclosure requirements for environmental information in CSR reports has created challenges in obtaining comprehensive greenwashing data across firms, potentially introducing measurement limitations to our study. However, with China’s recent issuance of the “Corporate Sustainability Disclosure Standards—Basic Standards (Trial)”, which marks the beginning of a systematic development of sustainability disclosure standards in China, future research could leverage the phased implementation of these standards, progressing from listed to non-listed companies, large firms to SMEs, qualitative to quantitative requirements, and voluntary to mandatory disclosure, to examine whether the impact of private firms’ actual controllers’ foreign residency rights on greenwashing demonstrates significant differences before and after the mandatory sustainability disclosure regime becomes fully operational.

While our current analysis focuses on the moderating role of internal and external monitoring mechanisms in the relationship between controllers’ residency status and greenwashing, subsequent studies could enrich the governance perspective by incorporating legal and regulatory oversight dimensions to develop a more comprehensive framework for analyzing corporate environmental accountability. Exploring these future research directions could not only address the current study’s limitations but may also deepen our understanding of how institutional evolution shapes the nexus between corporate governance attributes and environmental disclosure practices.

Author Contributions

Conceptualization, X.Z., H.C. and A.S.; methodology, X.Z., H.C. and A.S.; formal analysis, X.Z.; resources, X.Z. and H.C.; data curation, A.S. and X.Z.; writing—original draft, X.Z. and A.S.; writing—review and editing, X.Z. and H.C.; supervision, H.C.; project administration, H.C. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to the protection of intellectual property.

Conflicts of Interest

The authors declare no conflicts of interest.

Footnotes

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Tables

Table 1

Indicator system for corporate greenwashing.

Primary Indicator	Secondary Indicator
Governance and institutions	Environmental strategy and planning
	Environmental risk analysis
	Environmental regulations and implementation
External norms	Compliance with environmental laws
	Environmental certification and practices
	Environmental awards and recognition
	Environmental accidents or inspections
Internal evaluation	Environmental protection investment
	Energy consumption/reduction measures
	Wastewater discharge/reduction measures
	Waste gas emission/reduction measures
	Solid waste discharge/reduction measures
	Greenhouse gas emission/reduction measures
	Water resource consumption/reduction measures
	Other pollutant emission/reduction measures
	Other emission reduction measures
Green optimization	Green office initiatives
	Environmental public welfare
	Environmental education and training
	Technical upgrades and process innovation

Table 2

Variable definition.

Variables	Definitions
GWL	Greenwashing level, measured as defined in Section 3.2.2.
ID	Foreign residency rights of actual controllers; the dummy variable equals 1 if actual controllers possess foreign residency rights, and 0 otherwise.
Size	Firm size; i.e., logarithm of total assets.
Lev	Financial leverage; i.e., the ratio of total liabilities to total assets.
ROA	Profitability; i.e., the ratio of net profit to total assets.
Growth	Growth opportunity; i.e., (current-year operating revenue/previous-year operating revenue) − 1.
Ato	Total asset turnover; i.e., operating revenue divided by average total assets.
Cashflow	Cash flow ratio; i.e., net cash flow from operating activities divided by total assets.
Fixed	Fixed asset ratio; i.e., net fixed assets divided by total assets.
Indep	The proportion of independent directors; i.e., the number of independent directors divided by the total number of board members.
Top5	Ownership concentration; i.e., the percentage of shareholding of the top five shareholders.
Balance	Equity restriction; i.e., the ratio of the second largest shareholder’s ownership to the largest shareholder’s ownership.
MB	Book-to-market ratio; i.e., book value divided by market capitalization.
Listage	Listing age; i.e., the natural logarithm of (listing years + 1).
Slack	Slack resources; i.e., current assets divided by current liabilities.
Area 1	Western region dummy; the dummy variable equals 1 if it is headquartered in western China, and 0 otherwise.
Area 2	Central region dummy; the dummy variable equals 1 if it is headquartered in central China, and 0 otherwise.

Table 3

Descriptive statistics.

Variables	N	Mean	S.D.	Min	p25	p50	p75	Max
GWL	924	0.449	0.194	0.075	0.293	0.447	0.606	0.894
ID	924	0.140	0.347	0	0	0	0	1
Size	924	22.546	1.150	20.213	21.718	22.465	23.316	25.419
Lev	924	0.379	0.175	0.042	0.249	0.376	0.508	0.772
ROA	924	0.068	0.064	−0.122	0.028	0.060	0.105	0.298
Ato	924	0.705	0.411	0.117	0.448	0.627	0.860	2.790
Cashflow	924	0.076	0.064	−0.083	0.035	0.07	0.113	0.265
Fixed	924	0.264	0.135	0.046	0.153	0.248	0.360	0.622
Growth	924	0.199	0.417	−0.360	0.003	0.117	0.271	2.894
Indep	924	0.371	0.048	0.333	0.333	0.333	0.429	0.500
Top5	924	0.511	0.162	0.169	0.392	0.503	0.616	0.908
Balance	924	0.370	0.285	0.016	0.134	0.293	0.598	0.999
BM	924	0.891	0.695	0.110	0.410	0.701	1.141	3.741
Listage	924	2.241	0.665	0.693	1.792	2.398	2.773	3.258
Slack	924	2.627	2.951	0.422	1.115	1.700	2.846	18.821
Area 1	924	0.127	0.333	0	0	0	0	1
Area 2	924	0.170	0.376	0	0	0	0	1

Table 4

The effect of foreign residency rights on corporate greenwashing.

Variables	(1)	(2)
	GWL	GWL
ID	0.053 ***	0.061 ***
	(2.93)	(3.52)
Size		−0.055 ***
		(−6.77)
Lev		0.069
		(1.21)
Roa		−0.287 **
		(−2.18)
Ato		0.064 ***
		(3.72)
Cashflow		0.176
		(1.51)
Fixed		−0.238 ***
		(−4.69)
Growth		−0.019
		(−1.27)
Indep		−0.102
		(−0.84)
Top5		−0.093 **
		(−2.21)
Balance		−0.024
		(−1.14)
Bm		0.009
		(0.74)
Listage		0.032 ***
		(2.72)
Slack		0.005 **
		(1.98)
Area 1		−0.020
		(−1.14)
Area 2		0.031 *
		(1.88)
_cons	0.479 ***	1.765 ***
	(9.25)	(9.96)
Year	Yes	Yes
Industry	Yes	Yes
N	924	924
Adj. R2	0.109	0.240

Note: *, **, and *** represent significance at levels of 10%, 5%, and 1%, respectively, and t-statistics are shown in parentheses.

Table 5

Robustness tests.

Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
	Alternative Dependent Variable	Alternative Independent Variable	Firms with an Actual Controller	Samples Excluding Two Provinces	Samplesin Two Industries	LagIdentification	HeckmanSelectionModel	Include Omitted Variables
	RGWL	GWL	GWL	GWL	GWL	GWL	GWL	GWL
ID	1.062 ***		0.133 ***	0.051 **	0.099 ***	0.060 ***	0.054 ***	0.060 ***
	(4.32)		(5.79)	(2.49)	(4.57)	(2.89)	(3.06)	(3.46)
RID		0.072 ***
		(3.54)
Controls	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
IMR							0.294 **
							(2.51)
P ol itical								−0.015
								(−1.22)
_cons	15.659 ***	1.756 ***	1.784 ***	1.602 ***	1.702 ***	2.030 ***	1.005 ***	1.787 ***
	(6.33)	(9.91)	(8.02)	(8.09)	(8.10)	(9.56)	(2.97)	(10.04)
Year	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Industry	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
N	924	924	589	769	606	703	924	924
R2/Adj. R2	0.1479	0.241	0.279	0.228	0.251	0.237	0.245	0.241

Note: *, **, and *** represent significance at levels of 10%, 5%, and 1%, respectively, and t-statistics are shown in parentheses.

Table 6

Additional analysis.

Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)
	Direct Control	Indirect Control	HeavilyPolluting Industry C1	Heavily Polluting Industry C2	Internal Oversight	Media Supervision	Audit Regulation	Long-Term Effects
	GWL	GWL	GWL	GWL	GWL	GWL	GWL	GWLt +1	GWLt +2	GWLt +3
ID	0.205 ***	0.033	0.179 **	0.075 ***	0.289 ***	0.307 ***	1.124 ***	0.060 ***	0.084 ***	0.088 ***
	(6.23)	(1.62)	(1.99)	(3.57)	(2.97)	(3.26)	(3.04)	(2.89)	(3.51)	(3.08)
IC					−0.004
					(−0.76)
ID × IC					−0.036 **
					(−2.38)
Media						−0.004
						(−0.42)
ID × Media						−0.048 ***
						(−2.64)
Lnfee							−0.006
							(−0.36)
ID × Lnfee							−0.076 ***
							(−2.88)
Controls	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
_cons	1.107 ***	1.824 ***	−0.174	1.764 ***	1.733 ***	1.631 ***	1.653 ***	2.030 ***	2.253 ***	2.120 ***
	(2.76)	(9.05)	(−0.34)	(8.44)	(9.75)	(8.64)	(8.36)	(9.56)	(9.51)	(8.08)
Year	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Industry	Yes	Yes	No	No	Yes	Yes	Yes	Yes	Yes	Yes
N	151	773	133	649	924	924	924	703	570	459
Adj. R2	0.530	0.238	0.396	0.215	0.246	0.246	0.247	0.237	0.256	0.250

Note: *, **, and *** represent significance at levels of 10%, 5%, and 1%, respectively, and t-statistics are shown in parentheses.

Appendix A

Table A1 reports the findings from our Pearson correlation analysis, revealing that while the correlation coefficient between actual controllers’ foreign residency rights (ID) and corporate greenwashing (GWL) is statistically insignificant, it nevertheless shows a positive numerical value, indicating directional alignment between these variables. Importantly, the selected control variables demonstrate statistically significant correlations with both the dependent variable (GWL) and the independent variable (ID). Their significant association with the key explanatory variable confirms that these controls are not extraneous factors, while their relationship with the outcome variable contributes meaningfully to enhancing model specification and explanatory power, collectively affirming the viability of our variable selection framework.

Table A1

Correlation matrix.

	GWL	ID	Size	Lev	Roa	Ato	Cashflow	Fixed	Growth	Indep	Top5	Balance	Bm	Listage	Slack	Area 1	Area 2
GWL	1
ID	0.0310	1
Size	−0.323 ***	−0.0200	1
Lev	−0.143 ***	−0.094 ***	0.569 ***	1
Roa	−0.081 **	−0.0440	0.00400	−0.356 ***	1
Ato	0.140 ***	−0.081 **	−0.092 ***	0.113 ***	0.185 ***	1
Cashflow	−0.055 *	−0.056 *	0.0530	−0.186 ***	0.530 ***	0.134 ***	1
Fixed	−0.138 ***	0.00200	0.100 ***	0.248 ***	−0.193 ***	0.0250	0.141 ***	1
Growth	−0.087 ***	0.069 **	0.089 ***	0.075 **	0.269 ***	0.201 ***	0.071 **	−0.075 **	1
Indep	−0.0280	0.0120	0.0490	0.060 *	−0.0320	−0.0320	−0.0200	−0.0520	0.0230	1
Top5	−0.136 ***	0.063 *	0.0400	−0.070 **	0.176 ***	0.0350	0.117 ***	−0.097 ***	0.088 ***	0.111 ***	1
Balance	−0.0110	0.123 ***	−0.070 **	−0.167 ***	0.0520	−0.064 *	−0.0100	−0.143 ***	0.0490	−0.086 ***	0.092 ***	1
Bm	−0.119 ***	−0.112 ***	0.527 ***	0.570 ***	−0.340 ***	0.0100	−0.134 ***	0.309 ***	−0.082 **	−0.00200	−0.141 ***	−0.203 ***	1
Listage	−0.0310	−0.063 *	0.463 ***	0.243 ***	−0.064 *	−0.060 *	0.092 ***	0.067 **	−0.071 **	0.063 *	−0.415 ***	−0.136 ***	0.350 ***	1
Slack	0.136 ***	0.090 ***	−0.336 ***	−0.656 ***	0.274 ***	−0.149 ***	0.094 ***	−0.332 ***	−0.061 *	−0.0470	0.165 ***	0.233 ***	−0.347 ***	−0.226 ***	1
Area 1	−0.096 ***	0.0160	0.080 **	0.084 **	0.0420	−0.124 ***	−0.00300	0.0120	0.0390	0.0390	0.062 *	0.00400	−0.0240	0.055 *	−0.0260	1
Area 2	0.100 ***	−0.107 ***	0.0400	0.00600	0.0320	−0.00400	−0.0300	−0.108 ***	−0.0180	−0.0120	−0.133 ***	−0.0530	−0.0460	0.163 ***	0.0130	−0.172 ***	1

Note: *, **, and *** represent significance at levels of 10%, 5%, and 1%, respectively.

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