Can Financial Constraints and Regulatory Distance Reduce Corporate Environmental Irresponsibility?

Abstract

As global environmental problems become increasingly severe, corporate social (environmental) responsibility has become a hot topic in research, but there is still a lack of clear understanding of corporate environmental irresponsibility behavior and the driving factors behind this behavior. Our research aims to reveal the factors affecting corporate environmental irresponsibility from both internal and external perspectives. Inside enterprises, financial constraints will affect the degree of capital adequacy and thus affect the environmental behavior of enterprises. Externally, the fulfillment of corporate environmental responsibility will be affected by external regulatory pressure. Taking 399 A-share listed companies in China’s heavily polluting industries as the research objects, this paper empirically analyzes the influence paths and internal mechanisms of financial constraints and regulatory distance on corporate environmental irresponsibility, and it further divides regulatory distance into physical regulatory distance and power regulatory distance. This paper’s findings show that both financial constraints and physical regulatory distance were positively correlated with corporate environmental irresponsibility in China, and that the positive correlation between physical regulatory distance and corporate environmental irresponsibility was more significant in non-state-owned enterprises. In addition, financial constraints and regulatory distance have a complementary effect on corporate environmental irresponsibility. These findings can reduce the environmental risks posed by enterprises and help them to avoid environmental irresponsibility.

1. Introduction

At the current stage of rapid economic development in China, domestic enterprises are presented with many external development opportunities, and most of them have a strong impulse to expand. Compared with western countries, financing constraints are common in Chinese enterprises. The capital market is one of the external factors that influences the environmental behavior of enterprises. Financial constraints can have a negative impact on the business. For example, financial constraints restrain business innovation [1,2,3], increase financial irregularities in enterprises [4], and affect corporate social responsibility [5].

With the increasing awareness of global environmental protection, stakeholders are requiring companies to take on more social and environmental responsibilities, and calls for corporate social responsibility and environmental responsibility are rising [6,7,8]. Managers, companies, governments, and other stakeholders are increasingly paying attention to how to improve corporate environmental responsibility. In fact, such discussion is a necessity at higher levels in the organization. When corporate environmental irresponsible behavior occurs, it can be difficult to discuss the responsibility issue at a higher level. It can be difficult to move beyond the basics to consider broader issues. Only after ensuring that companies do not engage in environmentally irresponsible behavior can there be a basis for exploring the possibility of improving corporate environmental responsibility. Jones and Bow (2009) suggest that corporate social irresponsibility (CSIR) is often reactive rather than proactive in dealing with the company’s problems, which can, in extreme cases, involve violation of the law [9]. Lin-Hi and Muller (2013) suggest that corporate social responsibility has the dual connotation of “doing good” and “not doing bad”, while corporate social negligence emphasizes that the behavior does not conform to moral or legal constraints and creates actual or potential negative impacts on society, that is, “doing bad things” [10]. Consistent with the above points, corporate environmental irresponsibility (CEIR) is not just about “not doing good”. We define corporate environmental irresponsibility (CEIR) as enterprises, out of self-interest or for other reasons, not pursuing overall social benefit, and failing to assume responsibility for environmental protection, while, at the same time, in the pursuit of economic benefits, excessively consuming environmental resources, wantonly discharging pollutants, avoiding effective environmental governance, generating negative effects on the ecological environment, and causing damage or loss through short-termist behavior. In essence, corporate environmental irresponsibility (“doing bad things”) and corporate environmental responsibility (“doing good things” and “not doing bad things”) are not two sides of the same issue. Corporate environmental irresponsibility is more concerned with the fact that a company’s behavior does not conform to ethical norms or legal constraints and causes, or potentially causes, negative effects on others [11].

Financial slack theory implies that any company has an investment hierarchy. The investment needs of the core business are ranked first, with a view to meeting the performance requirements of the business and the needs of stakeholders [12,13,14], while “discretionary” actions, such as CSR activities and environmental responsibility, are placed last [15]. When an enterprise is faced with significant financial constraints, it is short of funds and its overall financial situation is problematic. In order to maintain the operation, the enterprise may engage in environmentally negligent behavior. The “certainty effect”, proposed by prospect theory, implies that losses or gains which are certain will have a stronger behavioral effect than minor losses or gains [16,17,18]. If the basic business needs of an enterprise are not met, this is likely to cause a deterioration of business functioning, or even to result in stoppage of production or bankruptcy. However, the consequence of corporate environmental negligence is to violate environmental laws and regulations, potentially leading to fines or orders to rectify [19], and it is very probable that no harms will be caused without them being discovered. However, the consequences of business deterioration for the enterprise are more serious than the consequences of corporate environmental negligence. Therefore, when finance is constrained, corporate decisions are made in accordance with prospect theory, and capital is directed towards basic business needs, potentially ignoring corporate environmental responsibility, and leading to corporate environmental irresponsibility.

In recent years, geographical factors have become an important research topic concerning capital markets [20,21,22,23], and distance is one of the geographical factors. Geographical factors cover many factors that relate to non-traditional finance, such as the degree of regional economic development and the financial environment, which have a significant impact on the cost of capital to companies in China’s immature economic environment. According to the theory of public regulation, capital markets have information asymmetry and strong external effects, so require government supervision [19]. There is a vast territory and very many listed companies in China which are scattered across various regions. However, regulatory resources are always limited, which results in wide variation in the regulatory distance between listed companies and the regulatory authorities. In view of the special background of China, in addition to physical distance, administrative level will also have an impact on the environmental behavior of enterprises [24]. The regulatory distance we discuss is based both on geographic regulatory distance and power regulatory distance. In addition, listed companies generally present principal–agent problems, reflecting their own occupation and salary concerns [25,26,27]; with a view to increasing the value of options in the short term [28,29], managers may conduct illegal operations, and the potential for environmental irresponsibility will increase.

The viewpoint described above is founded on two predictions. The first is that regulatory distance exacerbates the impact of information asymmetry [30,31]. With increase in regulatory distance, regulators need to spend more time, energy, money, and other resources to collect relevant information on listed companies, which weakens the ability of regulators to obtain corporate environmental protection information. Since modern communication technology is very advanced, the regulatory authorities can conduct supervision through the network, and the COVID-19 pandemic has increased the opportunity for people to work at home [32], but regulatory distance still hinders the transmission of information. Video conferencing, network supervision and other methods can also have problems of information security [33], information reliability and so on. Supervision on-line cannot completely replace on-site supervision; this is because information obtained by on-site supervision is more reliable and can include relevant “soft information”. Therefore, even during the COVID-19 period, in order to effectively regulate, the environmental supervision working group carried out on-site monitoring activities on key issues in environmental protection. The second prediction is that regulatory distance weakens regulatory deterrence. Regulatory distance affects the institutional pressure perceived by enterprises [34] and the transmission of deterrent signals. Enterprises at a longer regulatory distance are more likely to experience weaker pressure from environmental regulations and are more likely to engage in environmentally negligent behavior because of their less effective regulation. That is, the closer the regulatory distance is, the higher the level of governance, the stronger the regulatory intensity, the higher the degree of enterprise self-discipline, the smaller the possibility of environmental irresponsibility, and the more standardized the enterprise’s environmental behavior.

Fraud triangle theory suggests that the causes of fraud usually comprise three factors: pressure, opportunity, and excuse [35,36]. Although environmental irresponsibility is not as serious as corporate fraud, the influencing factors of environmental misconduct can be explained by the fraud triangle theory, because environmental irresponsibility also includes the three key elements that constitute the fraud triangle. Financial constraints correspond to pressure, and regulatory distance provides opportunities for enterprises. Since the consequences of environmentally irresponsible behaviors are smaller than those of declining performance, enterprises will rationalize their environmentally irresponsible behaviors. When the company is constrained by financing, the company is faced with greater capital pressure, which causes the company to orient capital to the basic business and increases the motivation for corporate environment irresponsibility. When the regulatory distance is great, the degree of information asymmetry increases and regulatory deterrence decreases, which creates the opportunity for companies to engage in environmental misconduct. Therefore, when firms are constrained by financing, firms with greater regulatory distance are more likely to engage in environmental misconduct.

Gender is an important sub-topic in corporate social responsibility research [37,38,39], such as the gender profile of senior executives. The gender diversity of senior executives is an important internal environmental irresponsibility driving factor. When discussing gender diversity, we consider internal passive driving factors (financial constraints) and external driving factors (regulatory distance) above but do not discuss internal active driving factors. The gender diversity of senior executives is included here, not only to make the paper more comprehensive, but also because the enterprise is managed by senior executives. Managers can gain some understanding of environmental irresponsibility through this study. According to the theory of gender diversity, women pay more attention to the interests of stakeholders [40,41,42]. When a large proportion of senior executives are women, the enterprise pays more attention to the needs of stakeholders [43,44]. When financial constraints occur, managers are less likely to pursue profit maximization at the expense of the environment, thus inhibiting corporate environmental irresponsibility. Similarly, if the company is far away from the regulatory authority, but there are more female executives in senior management positions, out of concern for stakeholders managers will voluntarily disclose more environmental information, thus reducing the possibility of environmental misconduct.

To test our predictions, we took A-share listed companies in high-pollution and high-risk industries in China from 2012 to 2018 as sample objects. Based on previous studies, we proposed the concept of corporate environmental failure for the first time, constructed a corporate environmental failure scale, and empirically tested the impact of financial constraints and regulatory distance on corporate environmental failure. Furthermore, the interaction between financial constraints and regulatory distance was evaluated, and the moderating effect of executive gender diversity was further explored. In addition, the study also divided the research samples into state-owned enterprises and non-state-owned enterprises, according to their different property rights, and performed group tests.

The main research questions of this paper are: How do financial constraints and regulatory distance affect corporate environmental misconduct? Is there an interaction between the effects of financial constraints and regulatory distance on corporate environmental failure? How does executive gender diversity mediate the relationship among financial constraints, regulatory distance, and corporate environmental irresponsibility? By answering these questions, this paper provides different ideas for enterprises to improve their environmental responsibility behavior and addresses the basic problems of enterprise environmental irresponsibility. This study contributes to existing literature in several ways: First, we add to the limited extant literature by focusing on the association among financial constraints, regulatory distance, and corporate environmental irresponsibility. Secondly, unlike prior studies that concentrate on corporate environmental responsibility, this paper extends prior studies by examining the opposite side of corporate environmental irresponsibility. We study the driving factors of environmental irresponsibility to enrich the related corporate social (environmental) responsibility research. Third, this paper, based on fraud triangle theory, comprehensively considers the influence of pressure factors and opportunity factors on corporate environmental negligence from macro and micro perspectives, and enriches the research on fraud triangle theory.

The remainder of this paper is organized as follows: The next section reviews the literature and proposes relevant research hypotheses. After presenting the method, we describe our data collection methods, measurement of main variables, and research models. Then, we outline the empirical results. Finally, we introduce the conclusions, meanings, and limitations of the research, and we offer some suggestions for future research.

2. Literature Review and Hypotheses

2.1. Financial Constraints and Corporate Environmental Irresponsibility

The literature has reported that access to resources may promote corporate environmental responsibility decisions and it is crucial for determining whether companies are able or willing to avoid socially unacceptable behaviors. Financial constraints impact the expected future profitability and financing capabilities of a company. Due to the imperfections of the capital market, financial constraints are related to the company’s capital supply, internal capital opportunity cost, and external capital cost [45,46]. Existing research mainly focuses on the economic consequences of financial constraints. For example, companies with financial constraints face higher capital costs and are more likely to suspend R&D projects [47] and increase corporate risk. Their corporate value is reflected in stock returns [48]. In addition, the academic community has carried out research on financial constraints from the perspective of how they affect corporate decision-making behavior, such as exploring whether financial constraints affect corporate innovation behavior and innovation input [1,3,49], and whether they affect corporate environmental behavior and the development of CSR activities [50]. A large number of previous studies on the relationship between corporate environmental behavior and financial performance, based on information asymmetry and reputation mechanisms [51,52,53], posit that higher corporate social responsibility performance can attract investment by (1) reducing the information asymmetry of external information users, and (2) establishing a good corporate image and reducing financial costs, thereby improving financial performance [54]. The causal relationship between the two (corporate social responsibility and investment) may develop in either direction, i.e., the financial status of the enterprise can predict the environmental behavior of the enterprise [55].

Corporate environmental responsibility requires investment. When there is a lack of financial support, environmental responsibility cannot be fulfilled. When there is a shortage of funds, the enterprise may even engage in environmentally irresponsible behavior. According to financial relaxation theory, financial restraints may affect corporate investment preferences [56]. Due to financial constraints, limited financing, and weak profitability, companies will prioritize possible investment opportunities and may invest more funds into basic business needs [57,58]. Only the financial resources that remain idle will be used to fulfill environmental responsibilities. When managers believe that the company’s future profitability is considerable, the company tends to assume more social and environmental responsibilities; that is, expected financial capabilities affect the company’s environmental behavior decisions [59,60,61,62]. Generally, financially constrained companies cannot spend too much money on the performance of their environmental responsibilities. They may have a limited awareness of environmental protection [63,64], and they may even sacrifice the environment in exchange for profits, so the potential for environmental irresponsibility for these companies is high. On the other hand, the “certainty effect” of prospect theory predicts that certain losses or gains have stronger behavioral effects than slight losses or gains [65]. Failure to meet the basic business needs of enterprises is likely to cause the deterioration of business conditions, or even ceasing of production and bankruptcy, but the worst scenario of social or environmental negligence only entails violation of environmental laws and regulations, resulting in fines or ordered rectification, and normal production and operation can still be maintained. There is also the possibility that environmental harm may not be discovered and cause no loss to the company; after all, corporate environmental protection behavior is mostly by mandatory disclosure, and the supervision system is not perfect. Therefore, when finances are constrained, corporate decision-making is influenced by prospect theory and tilts toward basic business needs to a greater extent. Accordingly, this article proposes the following hypothesis:

Hypothesis 1 (H1).

Financial constraints are positively correlated with corporate environmental irresponsibility.

2.2. Regulatory Distance and Corporate Environmental Irresponsibility

Although there is less literature on the direct impact of regulatory distance on corporate environmental irresponsibility, relevant studies on corporate social responsibility, environmental information disclosure, and corporate environmental responsibility can provide guidance and reference. Long regulatory distance means information asymmetry and increased regulatory cost, and it is more difficult for the government to regulate the behavior of enterprises, especially as the environmental behavior cannot be reflected in financial statements. Therefore, long regulatory distance will provide opportunities for enterprises to engage in environmentally irresponsible behaviors. From the perspective of geographical factors, regulatory distance measures the distance between the company’s location and the local regulatory authorities, corresponding to the physical regulatory distance [66]. From the perspective of the government, regulatory distance reflects the distance between the controller level of an enterprise and central government, and represents the physical distance between the enterprise and the supervisory powers [67]. The higher the government level, the easier it is for companies to obtain information, technical resources, and political connections in the development process [68,69,70,71]. For example, the political connection between central enterprises and the government is significantly stronger than that of other (non-centralized) companies [72,73]. However, based on the theory of the reciprocal exchange of social capital [74], the government not only provides enterprises with various resources [75], but also places higher social expectations on enterprises and improves their legitimacy [76]. This paper argues that the regulatory distance between regulators and listed companies can affect corporate environmental irresponsibility in at least three respects.

First, regulatory distance affects the degree of information asymmetry. Regulatory distance affects corporate environmental irresponsibility by influencing information asymmetry between regulators and enterprises, which is called the regulatory information effect. On the one hand, the increase in geographic distance and regulatory power distance will cause the stakeholders to spend more human, material, and financial resources to collect enterprise-related information [77], which weakens the information acquisition ability of regulatory authorities and increases the degree of information asymmetry [78,79]. On the other hand, unlike financial information, environmental information does not have specific disclosure norms and standards, and it is difficult to disclose environmental breaches in a timely and effective manner [80]. In the case of limited human and material resources, geographic distance is not conducive to information transmission and face-to-face communication between regulatory agencies and enterprises [78], and this aggravates the “soft information asymmetry” [81], which is likely to affect communication of real information about the company’s violations. Even if digitization processes have enhanced the effectiveness of regulation, it has been undermined by the poor penetration of modern information technology. Environmental problems in economically developed and densely populated areas can be effectively supervised, but in remote, under-developed, and poor areas, even in the suburbs around cities, the government still relies on direct implementation of environmental regulations. If a company’s environmental irresponsibility is exposed, the company is likely to face regulatory punishment and a damaged reputation [82,83], so managers tend to conceal, or postpone release of, this information [84]. The further the distance from the regulatory authorities, the more likely management will be opportunistic in avoiding bearing environmental responsibilities, in order to maximize profits. This increases the probability of corporate environmentally irresponsible behavior. Conversely, regulatory authorities with geographical proximity can communicate with enterprises more conveniently and closely, obtain information about the business dynamics and environmental behavior of enterprises in a timely and accurate way, and reduce the adverse effects caused by information asymmetry. Similarly, when an enterprise is controlled by the government, the power regulatory distance is close, and the supervision department does not need to rely on layers of reports to obtain the enterprise environment information, which reduces the possibility of information distortion or falsification. It is worth noting that in China, although the largest shareholder of state-owned enterprises is the government, the government does not interfere in the normal production and operation of enterprises to a great extent and only intervenes when the market is out of balance. Therefore, state-owned enterprises also need to accept government supervision to influence the behavior of enterprises which ordinarily operate largely according to their own decision-making.

Second, regulatory distance affects the intensity of regulatory deterrence. We describe the regulatory deterrence effect as the mechanism by which regulatory distance affects corporate environmental behavior by influencing the degree of deterrence experienced by managers. For enterprises, legitimacy endows the enterprise with legal status and the right to use resources. To maintain legitimacy, enterprise behavior must always be consistent with the social value system [85]. Against the unique background of China, the government’s environmental policy has an important impact on regulating enterprises’ environmental behavior, and this policy provides an external reminder and institutional deterrent effect on managers’ decision-making behavior. When environmental policies are passed from the supervisory authority to the enterprise, the supervisory distance will have a differential impact on the communication process and the results. The closer to the regulatory agency, the higher the level of government control, the stronger the deterrence, the greater the institutional pressure the enterprise will feel, and the more likely it will be that executives will feel the presence of regulatory agencies and assume more environmental responsibilities. Proximity of regulatory authorities may reduce, to a certain extent, the enterprise’s behavior of concealing bad news; thus, such proximity may serve as an indirect form of corporate environmental behavior regulation [86]. In general, the regulatory distance will affect the institutional pressure perceived by enterprises and affect the transmission of deterrence signals.

Third, regulatory distance affects the intensity of ecological opportunism. Ecological opportunistic behavior is a concrete manifestation of opportunistic behavior in the field of environmental protection law. The shortcomings of human rationality, as well as information asymmetry, limit the comprehensive and effective monitoring of corporate environmental behavior [87]. Therefore, companies may make full use of this to conduct opportunistic environmental information disclosure. For companies with remote geographic locations and low government levels, if their managers have an opportunistic psychology, they may feel that even if they have committed certain environmental derelictions, they will be less likely to be inspected and exposed. In addition, the cost of supervision is high, so environmental irresponsibility is more likely to occur and to occur more frequently. At the same time, management opportunism will change its corporate environmental behavior based on changes in the external situation and the corporate environment. Accordingly, this article proposes the following hypotheses:

Hypothesis 2 (H2).

Regulatory distance is positively correlated with corporate environmental failure.

Hypothesis 2a (H2a).

Physical regulatory distance is positively correlated with corporate environmental irresponsibility.

Hypothesis 2b (H2b).

Power regulatory distance is positively correlated with corporate environmental irresponsibility.

2.3. The Moderating Effect of Gender Diversity in Executives

The driving factors of environmental irresponsibility are external and internal. Above, we discussed internal passive driving factors (financial constraints) and external driving factors (regulatory distance). This paper intends to explore the causes of environmental irresponsibility from the perspective of internal active factors in a more comprehensive way. According to upper echelons theory, corporate environmental behavior is influenced by corporate executives, and the characteristics of executives are likely to have an impact on corporate environmental behavior. Therefore, it is important to consider the impact of executive gender characteristics on corporate environmental irresponsibility here. Gender plays an important role in influencing individual decisions. In companies, the gender of senior executives and the proportion of female directors are important determinants of corporate policies. The impact of executive gender on corporate social responsibility, charitable giving, and environmental behavior has been studied. Bear and Rahman et al. (2010) explored how the diversity of board resources and the number of women on the board affected a company’s corporate social responsibility (CSR) rating [88]. Research has shown that the number of women on the board of directors has a positive correlation with commitment to CSR, and that women were more inclined to make decisions in line with social responsibility. Post et al. (2011) found that when there are three or more female directors on the board of directors, enterprises score higher on environmental intensity scale measures [89]. Mcguinness and Vieito et al. (2017) used data from Chinese listed companies from 2009 to 2013 to study the impact of senior executive gender and foreign ownership on corporate social responsibility performance [90]. The results showed that gender balance among senior executives is positively correlated with corporate social performance; that is, the more balanced the gender ratio of the senior executives, the higher the corporate social performance is likely to be. Further research has shown that companies with female executives have improved social performance. Seto-Pamies (2013) analyzed the impact of board diversity on corporate social responsibility and posited that female directors could play a strategic role in the fulfillment of corporate social responsibility [91]. This study found that the higher the proportion of female directors, the more corporate social responsibility would be assumed. Although there is no consensus among the relevant research as to whether gender diversity helps to reduce the incidence of poor enterprise environment responsibility behavior, we can draw some lessons about the effects of executive gender diversity on corporate social responsibility. Based on research in the field of charitable giving, we may differentiate the effect of executive gender diversity on financial constraints and supervision from the regulating effect created by the relationship between executive gender and enterprise environment responsibility behavior.

Gender diversity theory acknowledges that women are more sensitive to risk perception, pay more attention to the rights and interests of stakeholders, and care more about the needs of others. Compared with men, women show more kindness and care, are more likely to accept a moral code, tend to show a more conservative and cautious attitude towards corporate decisions, more actively respond to the call of social responsibility, are more likely to carry out correct environmental protection behavior, and are less likely to operate in an environmentally irresponsible manner. In addition, gender diversity also affects the supervisory and management functions of the board of directors [88]. The participation of female executives helps to break up the structure of the existing executive group, reduce the demographic difference between the board of directors and management, and more effectively monitor the behavior of the board of directors [92,93,94]. Therefore, if the company encounters financial constraints, but the number of female executives among the senior management members is significant, it is unlikely that the company will seek to meet only the core business needs and abandon its investment in environmental protection. In the same way, if the company is located far away from the regulatory authorities, but a significant number of female executives hold senior management roles, they will voluntarily disclose more environmental information, engage in more environmental behaviors, and ensure that their business and production activities are within the requirements of environmental protection standards. Ecological opportunism and maverick psychological desires are weakened, and the possibility of environmental irresponsibility behavior is reduced. Accordingly, this article proposes the following hypotheses:

Hypothesis 3a (H3a).

The gender diversity of executives will weaken the positive correlation between financial constraints and corporate environmental irresponsibility.

Hypothesis 3b (H3b).

The gender diversity of executives will weaken the positive correlation between regulatory distance and corporate environmental irresponsibility.

3. Data and Methods

3.1. Sample Selection and Data Sources

This article uses China’s 2012–2018 consecutively issued corporate social responsibility reports on the A-share main board listed companies in heavy polluting industries as the initial sample. The selection of China’s heavy pollution industries is based on the “Guidelines for Environmental Information Disclosure of Listed Companies” published by the Ministry of Environmental Protection on 14 September 2010. It comprises mainly the five major industry categories shown in

Table 1. Industry distribution of sample companies.

Industry Category	Industry Code	Quantity	Percentage (%)
Mining industry	B06–B12	36	9.02
Manufacturing	C13–C43	317	79.45
Electricity, heat, gas and water production and supply industry	D44–D46	38	9.52
Construction, real estate	E47–E50	6	1.50
Water conservancy, environment and public facilities management industry	N76–N78	2	0.51
		399	100

. The following samples were removed: (1) ST and *ST companies; (2) Listed companies with 2012–2018 annual report or social responsibility report or sustainable development report missing; (3) Listed companies with missing financial data from 2012 to 2018. Finally, 399 listed companies were selected as the research samples. Listed companies were used as research samples, and their industry distribution is shown in Table 1. The corporate environmental irresponsibility data was based on the constructed corporate environmental irresponsibility scale, along with manually reviewed corporate social responsibility reports and sustainability reports. The data on financial constraints was drawn from the CSMAR database, and was further supplemented by the annual reports of the listed companies. The physical distance involved in the regulatory distance was entered manually as the registered locations of the listed company and the local regulatory authority (Ecology and Environment Bureau) to calculate the distance between the two places. The power distance data was manually collected by the controller of the Cathay Security Database (CMSAR). In addition, the data related to the control variables was collected through the RESSET database and the CSMAR database.

3.2. Variable Design

3.2.1. Dependent Variable

Based on the GRI Sustainability Report Guidelines (2006) and the Runling Global MCT Social Responsibility Report Rating System (2012), we summarized the research results of Clarkson et al. (2008), Du et al. (2016), and Du et al. (2014) [95,96,97]. As we can see in

Table 2. Corporate Environmental Irresponsibility (CEIR) Scale.

Measure Indicators	Item	Reference
A1: Establishment of corporate governance structure and management system	There is no environmental protection/pollution control management department	GRI Sustainability Report Guidelines (2006), Clarkson et al. (2008) [95]
	Lack of provisions for environmental practices applicable to suppliers or customers
	Stakeholders do not participate in the formulation of corporate environmental policies or in the process of environmental information disclosure
	Executive/employee compensation has nothing to do with environmental performance
	Failed to pass the environmental management system certification (ISO14001)
	The environmental risk prevention or emergency response system is not disclosed
A2: Credibility	No environmental report (ER), corporate social responsibility report (CSR), or GRI Report	Du et al. (2016) [96], Du et al. (2014) [97]
	The environmental performance report has not been verified by a third party
	No reference to the GRI Guidelines for Sustainability Reporting
	No independent audit of environmental performance and system has been conducted for a long time
	No environmental (energy saving) label product certification/environmental plan certification
	Not involved in specific industry associations or other environmental groups to improve the environment
	Not participating in voluntary environmental actions recognized by environmental protection authorities (organizing forums or donations)
A3: Environmental performance indicator	Failure to disclose their energy use or excessive energy use	Byun and Oh (2018) [98], Xu et al. (2016) [99]
	Failure to disclose their water use or excessive use
	Failure to disclose their emissions of greenhouse gases or other gases or emitting too much
	Failure to disclose their electricity use or excessive use
	Failure to disclose toxic/hazardous material/solid waste release stock or releasing too much
	Environmental emission performance of undisclosed waste gas, waste water, and waste residue (specific value)
	Undisclosed performance or poor performance with respect to land, resources, waste generation and management, biodiversity, or conservation
	There are environmental violations that have been exposed
	Subject to litigation for environmental damages
A4: Environmental spending	No information that environmental measures have resulted in cost savings for the company	Du et al. (2016) [96]
	Lack of funding for technology research and development or innovation to improve environmental performance or efficiency
A5: Vision and strategic proposition	No corporate environmental policy, environmental code of conduct, or stakeholder statement	Ioannou et al. (2016) [100], Mirvis et al. (2016) [101]
	No formal management system for environmental risks and performance or a statement of periodic review and assessment
	No statement of environmental performance assessment of environmental facilities/product development
	No statement of measurable targets for future environmental performance
A6: Environment profiles	Lack of an overview of the impact of business operations or products and services on the environment (EIA)	Du et al. (2014) [97]
	Lack of corporate or industry overview of environmental performance relative to industry peers
A7: Environmental initiatives	Lack of substantive information on employee training in environmental management and operations	Cuny (2016) [102], Jaggi et al. (2018) [103]
	No national environmental awards this year
	Failure to pass internal environmental audit or establish internal certification of environmental plan
	Negative treatment of environmental violation responsibility

, we retained their division of corporate environmental responsibility, integrated and adjusted the items in accordance with China’s national conditions, and improved and built a corporate environmental irresponsibility scale based on the available data to score enterprises in terms of their level of corporate environmental irresponsibility [95,96,97]. Corporate environmental irresponsibility was divided into 7 categories: corporate governance structure and management system settings, credibility, environmental performance indicators, environmental expenditures, vision and strategic propositions, environmental overview, and environmental advocacy activities. These 7 categories included a total of 33 items. The corporate environmental irresponsibility score represented the management activities of the company in terms of assumed environmental responsibility. If the sample company had not disclosed certain environmental information, it was assigned a value of 1 otherwise it was given a value of 0, and the corporate environmental irresponsibility score was summarized. The larger the score, the more serious the corporate environmental irresponsibility of the sample company. Because corporate environmental irresponsibility was reflected indirectly through various items, we calculated the Cronbach alpha coefficient to measure the internal consistency of the corporate environmental irresponsibility scale. The results showed that the alpha coefficient was 0.86, indicating that the scale was reliable.

3.2.2. Independent Variables

(1) Financial constraints

A financial constraint was defined as the expected future profitability and financing ability of the enterprise; this is different from simply the net worth or internal and external financing status of the enterprise. Unlike the commonly used KZ index, the WW index is consistent with firm characteristics associated with external finance constraints. Referring to the practice of Whited and Wu (2006) [104], we used the WW index to measure financial constraints. We comprehensively considered the impact of net cash flow, cash dividends, long-term debt, total assets, and sales growth rate, avoiding the subjectivity of sample selection and measurement errors. The larger the calculated WW index value, the higher the financial constraints of the enterprise.

WW = −0.091(CF/TA) − 0.062Divdum + 0.021(LTD/TA) − 0.044logTA + 0.102ISG − 0.035SG

Among them, CF is the company’s net operating cash flow at the end of the year; and Divdum indicates whether the company paid cash dividends in the year. If the cash dividend was paid, the value is 1; otherwise, it is 0. LTD refers to the total long-term debt of the company; TA is the total assets of the company at the end of the year; ISG is the sales growth rate of the company’s industry; and SG is the company’s sales growth rate.

(2) Physical regulatory distance

Physical regulatory distance refers to the straight-line distance between the physical location where a company headquarters is located and that of the local regulatory authority. Drawing on the basic ideas of Yao and Liang (2017), Yao and Yang (2017), and Kubick and Lockhart (2016) [24,105,106], this paper calculated the geographic distance between the registered place of a listed company and that of the local regulatory authority (Ecology and Environment Bureau). We used Baidu Maps, Google Maps, and other Internet tools to manually measure the distance between the registered location of the sample listed company and each regulatory authority to obtain the physical regulatory distance.

(3) Rights regulatory distance

The power regulatory distance refers to the administrative level distance between the company and the central government. Referring to the practices of Wang et al. (2018) and Li et al. (2018) [107,108], and based on “ultimate property rights theory”, this paper divided the enterprises into 5 types based on the actual controller data of the enterprise: central, provincial, city-level, county-level, and private enterprises are assigned a value of 1–5 to calculate the government level distance for the different types of enterprises. For example, if the company was controlled by the central government, it was assigned a value of 1. Based on this, the power regulatory distance was obtained.

3.2.3. Moderator Variables

Referring to the practices of Liu (2018) and McGuinness et al. (2017) [90,109], we used the proportion of female executives in the executive group (female executives divided by the total number of executives) to measure the gender diversity of enterprise executives.

3.2.4. Control Variables

This article refers to the practices of Hegde and Mishra (2019), Chen et al. (2019), McCarthy et al. (2017), and Patro et al. (2018) [110,111,112,113]. We began with the company characteristics and governance control, and we selected the asset-irresponsibility ratio, return on assets, and sales growth. The controlling variables included: ratio, leverage ratio, size of the board of directors, independence of the board of directors, average age of senior management, shareholding of the top 10 shareholders, duality, and annual and industry dummy variables.

3.3. Model Setting

Considering that this paper involves a dependent variable, the individual effect is not obvious, and the sample size is not large, multivariate OLS regression can simplify the regression process and can give a relatively accurate regression result. This paper refers to the research of Dhaliwal et al. (2011) [114] and establishes the following model for empirical testing:

$$CEI{R}_{i,t}={\alpha }_0+{\alpha }_{1}W{W}_{i,t}+\beta Contro{l}_{i,t}+{\epsilon }_{i,t}$$

(1)

$$CEI{R}_{i,t}={\alpha }_0+{\alpha }_{1}Distanc{e}_{i,t}+\beta Contro{l}_{i,t}+{\epsilon }_{i,t}$$

(2)

To study the moderating effects of executive gender diversification on the impact of financial constraints and regulatory distance on corporate environmental irresponsibility, we introduced executive gender diversification, and executive gender diversification and financial constraints, based on Model 1 and Model 2, respectively. We then considered the crossover of the gender diversity of executives and the regulatory distance to construct Models 3 and 4, which were used to test our results.

$$CEI{R}_{i,t}={\alpha }_0+{\alpha }_{1}W{W}_{i,t}+{\alpha }_{2}Board Gende{r}_{i,t}+{\alpha }_{3}W{W}_{i,t}\times Board Gende{r}_{i,t}+\beta Contro{l}_{i,t}+{\epsilon }_{i,t}$$

(3)

$$CEI{R}_{i,t}={\alpha }_0+{\alpha }_{1}Distanc{e}_{i,t}+{\alpha }_{2}Board Gende{r}_{i,t}+{\alpha }_{3}Distanc{e}_{i,t}\times Board Gende{r}_{i,t}+\beta Contro{l}_{i,t}+{\epsilon }_{i,t}$$

(4)

The definition and measurement of variables in the models are shown in

Table 3. Descriptive statistics of main variables.

Variables	Obs	Mean	Std. Dev.	Min	Max	p = 50%	p = 25%	p = 75%
CEIR	2793	24.525	5.577	4	31	26	22	29
WW	2793	−1.027	0.151	−6.776	−0.133	−1.029	−1.078	−0.983
Distance1	2793	20.656	24.376	0.16	151.1	11.4	6	25
Distance2	2793	3.35	1.648	1	5	3	2	5
BoardGender	2793	0.157	0.102	0	0.533	0.136	0.083	0.216
Lev	2793	0.458	0.195	0.014	1.352	0.465	0.309	0.606
ROA	2793	0.038	0.065	−0.927	0.59	0.031	0.010	0.064
Growth	2793	0.32	3.688	−2.683	179.164	0.075	−0.056	0.249
leverage	2793	0.186	0.147	0	0.757	0.169	0.063	0.281
Boardsize	2793	9.057	1.926	3	18	9	8	9
Boardindep	2793	0.369	0.053	0.231	0.667	0.333	0.333	0.4
Averageage	2793	50.043	2.923	40.35	61	50.06	48.05	52
OwnCon10	2793	56.835	15.723	10.555	98.588	56.82	45.59	67.74
Dual	2793	1.812	0.419	0	2	2	2	2

, where i represents the enterprise, t represents the year, and ${\epsilon }_{i,t}$ represents the error term. In addition, the Hausman test results show that this article is suitable for using fixed effects.

4. Empirical Analysis

4.1. Descriptive Statistics and Correlation Analysis

Table 3 shows the descriptive statistics of the main variables of the A-share listed companies in China’s heavy pollution industries. The statistical results show that the average value of corporate environmental irresponsibility was 24.525 and the minimum and maximum values were 4 and 31, respectively, which indicates that the heterogeneity of corporate environmental irresponsibility was significant, and the environmental irresponsibility of heavy pollution industries in China was relatively serious. The average number of financial constraints was −1.027 and the minimum and maximum values were −6.776 and −0.133, respectively, which also shows that the heterogeneity of financial constraints was significant. The average number of the regulatory distance was 20.656, while the minimum and maximum values were 0.16 and 151.1, respectively, which indicates that the overall regulatory distance was relatively small. China’s regulatory regime in some regions is relatively inadequate. The average number of the power regulatory distance was 3.35, which indicates that most of the heavy pollution enterprises in China were state-owned enterprises. The average number of the senior management diversification was 0.157, and the minimum value was 0, which indicates that most executives in Chinese enterprises were employed by state-owned enterprises. The proportion of female executives was still relatively low, and some enterprises had no female executives at all; thus, in some companies, male executives dominated the top management.

To identify whether the model constructed in this paper had serious multiple collinearity problems and to preliminarily test the correlation between variables, we conducted a Pearson correlation analysis and a Spearman correlation analysis on the main variables. The correlation coefficient matrix is shown in

Table 4. Correlation analysis results.

Variable	CEIR	WW	Distance1	Distance2	BoardGender	Lev	ROA	Growth	Leverage	Boardsize	Boardindep
CEIR	1	0.090 ***	−0.019	0.063 ***	−0.099 ***	−0.050 ***	−0.006	−0.011	−0.029	−0.058 ***	0.011
WW	0.023	1	0.098 ***	0.227 ***	0.222 ***	−0.243 ***	−0.139 ***	−0.037 ***	−0.179 ***	−0.230 ***	−0.036 *
Distance1	−0.006	0.016	1	0.439 ***	0.115 ***	−0.118 ***	0.093 ***	−0.006	−0.098 ***	−0.094 ***	−0.121 ***
Distance2	0.048 **	0.116 ***	0.404 ***	1	0.307 ***	−0.252 ***	0.153 ***	0.007	−0.187 ***	−0.243 ***	−0.041 **
BoardGender	−0.079 ***	0.100 ***	0.091 ***	0.314 ***	1	−0.178 ***	0.111 ***	0.057 ***	−0.115 ***	−0.246 ***	0.046 **
Lev	−0.041 **	−0.112 ***	−0.135 ***	−0.257 ***	−0.185 ***	1	−0.506 ***	−0.066 ***	0.797 ***	0.164 ***	−0.005
ROA	0.006	−0.052 **	0.036 *	0.091 ***	0.061 ***	−0.391 ***	1	0.013	−0.454 ***	−0.009	−0.003
Growth	0.036 *	−0.719 ***	−0.014	−0.011	0.014	0.037	−0.023	1	−0.117 ***	−0.015	0.039 **
Leverage	−0.032 *	−0.086 ***	−0.104 ***	−0.214 ***	−0.113 ***	0.776 ***	−0.330 ***	0.019	1	0.164 ***	−0.016
Boardsize	−0.048 **	−0.128 ***	−0.101 ***	−0.266 ***	−0.243 ***	0.191 ***	0.021	−0.007	0.166 ***	1	−0.347 ***
Boardindep	0.017	0.008	−0.105 ***	−0.006	0.082 ***	−0.020	−0.011	−0.009	−0.032 *	−0.358 ***	1

Note: the lower triangle is the Pearson correlation coefficient, and the upper triangle is the Spearman correlation coefficient; ***, **, and * are significant at the 1%, 5%, and 10% levels, respectively.

. The results show that there was a significant correlation between corporate environmental irresponsibility and multiple control variables, which indicated that the model was reasonable. The results of the Pearson correlation analysis and the Spearman correlation analysis showed that corporate environmental irresponsibility was positively correlated with financial constraints. The Spearman correlation analysis was significant at the 1% level (the correlation coefficient was 0.090). However, the Pearson correlation analysis failed to pass the significance test, which initially supports Hypothesis 1. However, there were differences in the results of the correlation analysis between corporate environmental irresponsibility and regulatory distance. The Spearman correlation analysis and the Pearson analysis correlation analysis showed that physical regulatory distance (distance1) was negatively correlated with corporate environmental dereliction (CEIR), but this result failed to pass the significance test. The power regulatory distance (distance2) was positively correlated with corporate environmental dereliction (CEIR), which was significant at the 1% (the correlation coefficient was 0.063) and 5% (the correlation coefficient was 0.048) levels. The correlation coefficients of the variables were all in the range of 0.5, which indicated that there were no serious multicollinearity problem.

4.2. Main Effects Test

4.2.1. Regression Test of Financial Constraints and Corporate Environmental Irresponsibility

We conducted a regression analysis according to Model 1. The regression results are shown in the full sample (column 1) in

Table 5. Financial Constraints Test Results of Corporate Environmental Irresponsibility Relationship (H1).

Variable	(1)	(2)	(3)	(4)	(5)
	Full Sample	State-Owned Enterprise	Non-State Enterprises	Constrained	Unconstrained
WW	1.844 *	0.517	4.780 **	8.763 ***	0.009
	(1.72)	(0.37)	(2.55)	(2.70)	(0.01)
Lev	−0.840	−3.762 ***	1.808	−5.361 **	0.876
	(−0.94)	(−2.90)	(1.40)	(−2.40)	(0.88)
ROA	1.173	5.739	−0.177	8.098	0.678
	(0.66)	(1.72)	(−0.08)	(1.39)	(0.36)
Growth	0.116 ***	0.080	0.100	0.329 ***	−0.281
	(2.72)	(1.51)	(1.06)	(3.35)	(−1.12)
Leverage	−0.163	2.759 *	−2.812	7.219 ***	−2.295 *
	(−0.14)	(1.88)	(−1.50)	(2.87)	(−1.79)
Boardsize	−0.028	−0.029	−0.081	0.011	−0.045
	(−0.45)	(−0.39)	(−0.65)	(0.11)	(−0.55)
Boardindep	1.511	−0.014	3.350	−2.367	2.934
	(0.71)	(−0.00)	(0.98)	(−0.52)	(1.20)
Averageage	−0.050	−0.025	−0.072	0.163 *	−0.074 *
	(−1.29)	(−0.40)	(−1.33)	(1.82)	(−1.71)
OwnCon10	−0.037 ***	−0.027 ***	−0.048 ***	−0.036 **	−0.035 ***
	(−5.20)	(−2.75)	(−4.54)	(−2.40)	(−4.12)
Dual	0.465 *	−0.103	0.856 ***	0.995 *	0.343
	(1.82)	(−0.25)	(2.59)	(1.68)	(1.21)
_cons	30.18 ***	29.39 ***	33.34 ***	27.24 ***	29.09 ***
	(14.32)	(8.78)	(9.05)	(5.38)	(10.60)
Industry	YES	YES	YES	YES	YES
Year	YES	YES	YES	YES	YES
F value	5.65	3.60	4.77	3.60	2.91
Adj R2	0.016	0.017	0.028	0.036	0.009
N	2793	1482	1311	698	2095

Note: The t statistic is in parentheses. ***, **, * represents significance at 1%, 5%, and 10% levels, respectively.

. It was found that financial constraints (WW) predicted corporate environmental irresponsibility. The regression coefficient for corporate environmental irresponsibility (CEIR) was 1.844, and it was significant, indicating that financial constraints were substantially related to corporate environmental irresponsibility. To explore whether the nature of property rights affected the relationship between financial constraints (WW) and corporate environmental irresponsibility (CEIR) behaviors, the study sample was divided into state-owned enterprises and non-state-owned enterprises. The results showed that in state-owned enterprises, financial constraints and corporate environmental irresponsibility were positively correlated, but this finding failed the significance test (column 2). Among non-state-owned enterprises, financial constraints were positively correlated with corporate environmental irresponsibility and were significantly correlated at the 5% level (column 3), indicating that the positive correlation between financial constraints and environmental failure existed only in non-state-owned enterprises. In addition, this paper ranked the companies according to the WW index, defining the top quarter of the companies as the financially restricted group, and denoting the remainder of the companies as the non-financially restricted group. An analysis by group was carried out. The results showed the following findings regarding financial constraints and the corporate environment. A significant positive correlation with irresponsibility was only significant in the financially constrained group (columns 4 and 5). In the financially constrained group, the correlation coefficient of financial constraints (WW) was 8.763, and it was significant at the 1% level. In the non-financially constrained group, the correlation coefficient of financial constraints (WW) was only 0.009, which failed the significance test. The data showed that the probability of environmental irresponsibility on the part of the group that was subject to financial constraints was 8 times that of the group/s not subject to such financial constraints. This indicates whether financial constraints strongly affect the probability of corporate environmental irresponsibility.

4.2.2. Regression Test of Regulatory Distance and Corporate Environmental Irresponsibility

To test whether the regulatory distance also caused an increase in corporate environmental irresponsibility behavior (H1), we conducted a regression analysis according to Model 2; the regression results are shown in

Table 6. Results of analysis of the regulatory distance and corporate environmental irresponsibility relationship (H2).

Variable	CER (H2a)			CER (H2b)
	Full Sample	State-Owned Enterprises	Non-State Enterprises	Full Sample	State-Owned Enterprises	Non-State Enterprises
Distance1	0.066 ***	0.017	0.078 ***
	(3.21)	(0.33)	(3.62)
Distance2				0.052	0.431 **	1.403
				(0.70)	(2.27)	(1.34)
Lev	−0.031	−1.506	0.900	−0.882	−4.104 ***	1.958
	(−0.02)	(−0.73)	(0.52)	(−0.99)	(−3.18)	(1.52)
ROA	1.748	7.805 **	0.289	0.766	5.933 *	−1.093
	(1.03)	(2.20)	(0.15)	(0.43)	(1.79)	(−0.51)
Growth	0.018	0.021	−0.017	0.062 **	0.063 **	0.038
	(0.78)	(0.80)	(−0.23)	(2.16)	(2.10)	(0.41)
Leverage	1.578	4.461 *	0.714	−0.196	3.185 **	−3.578 *
	(1.01)	(1.94)	(0.32)	(−0.17)	(2.16)	(−1.93)
Boardsize	−0.023	−0.043	0.020	−0.032	−0.035	−0.105
	(−0.22)	(−0.30)	(0.12)	(−0.51)	(−0.48)	(−0.85)
Boardindep	−0.705	2.758	−6.488	1.484	−0.327	2.911
	(−0.27)	(0.79)	(−1.52)	(0.69)	(−0.12)	(0.85)
averageage	−0.018	0.044	−0.068	−0.051	−0.017	−0.083
	(−0.30)	(0.46)	(−0.83)	(−1.28)	(−0.28)	(−1.54)
OwnCon10	−0.003	0.016	−0.020	−0.0390 ***	−0.025 **	−0.051 ***
	(−0.21)	(0.80)	(−1.30)	(−5.56)	(−2.53)	(−4.83)
Dual	0.196	0.860 **	−0.308	0.498	−0.002	0.870 ***
	(0.72)	(2.16)	(−0.80)	(1.92)	(−0.00)	(2.63)
_cons	23.99 ***	18.35 **	28.92 ***	28.36 ***	27.52 ***	22.67 ***
	(6.67)	(3.27)	(6.00)	(11.80)	(8.07)	(3.68)
Industry	YES	YES	YES	YES	YES	YES
Year	YES	YES	YES	YES	YES	YES
F-value	6.65	5.51	7.55	5.40	4.12	4.29
Adj R2	0.060	0.014	0.018	0.016	0.021	0.026
N	2793	1482	1311	2793	1482	1311

Note: the lower triangle is the Pearson correlation coefficient, and the upper triangle is the Spearman correlation coefficient; ***, **, and * are significant at the 1%, 5%, and 10% levels, respectively.

for the full sample (column 1 and column 3). It was found that the physical regulatory distance (Distance1) was positively correlated with corporate environmental irresponsibility (CEIR). When the company is farther from the local regulatory agency, the regulatory pressure and institutional pressure will be lower, and the possibility of environmental irresponsibility will be higher. Research hypothesis H2a was supported. The regression coefficient of the power regulatory distance (Distance2) and corporate environmental irresponsibility (CEIR) was 0.052, but the significance test was not passed, so research hypothesis H2b was not supported.

State-owned enterprises will be subject to political supervision by the central government and by other bodies, such as the National Audit Office, and they will also receive attention from domestic and foreign media and the public. As a result, their opportunism tendencies and environmental behavior will be more constrained, which will inevitably create greater pressure in terms of environmental policy and social governance. We explored whether the nature of property rights caused differences in the relationship between physical regulatory distance (Distance1), power regulatory distance (Distance2), and corporate environmental irresponsibility (CEIR); the results are shown in Table 6. In the sample of state-owned enterprises, the regression coefficient between the physical regulatory distance (Distance1) and corporate environmental irresponsibility (CEIR) was 0.017, but it failed the significance test. In the sample of non-state-owned enterprises, the physical regulatory distance (Distance1) and corporate environmental irresponsibility (CEIR) regression coefficient was 0.078, and it was significant at the 1% level, indicating that the positive correlation between physical regulatory distance and corporate environmental irresponsibility was more marked for non-state-owned enterprises. Similarly, the research results showed that the positive correlation between power regulatory distance (Distance2) and corporate environmental irresponsibility only pertained to state-owned enterprises.

4.3. Moderating Effect Test

4.3.1. The Moderating Effect of Financial Constraints on Corporate Environmental Irresponsibility

The gender diversity of executives affects corporate decision−making. Female executives are more inclined toward democratic or participatory management, assume more social and environmental responsibilities, and are more sensitive to environmental issues. Therefore, we performed a regression analysis on Model 3, and the regression results are shown in

Table 7. Test Results of the Moderating Effects of Executive Gender Diversity (H3a).

Variable	(1)	(2)	(3)
	Full Sample	State-Owned Enterprise	Non-State Enterprises
WW	2.923 *	3.322	8.653 **
	(1.68)	(1.54)	(2.18)
BoardGender	−6.503	−23.25	−18.41
	(−0.63)	(−1.62)	(−0.95)
WW × BoardGender	−9.061 *	−23.49 *	−21.96
	(−1.90)	(−1.73)	(−1.15)
Lev	−0.612	−3.780 ***	1.951
	(−0.68)	(−2.90)	(1.51)
ROA	0.850	5.017	−0.307
	(0.47)	(1.49)	(−0.14)
Growth	0.116 ***	0.089 *	0.0751
	(2.69)	(1.67)	(0.78)
Leverage	−0.305	2.713	−2.889
	(−0.27)	(1.84)	(−1.55)
Boardsize	−0.005	−0.021	−0.031
	(−0.07)	(−0.28)	(−0.25)
Boardindep	1.489	0.216	3.107
	(0.70)	(0.08)	(0.91)
averageage	−0.030	−0.010	−0.072
	(−0.78)	(−0.16)	(−1.34)
OwnCon10	−0.035 ***	−0.025 **	−0.046 ***
	(−4.92)	(−2.55)	(−4.41)
Dual	0.464 *	−0.132	0.797 **
	(1.82)	(−0.32)	(2.41)
_cons	29.52 ***	31.25 ***	36.21 ***
	(11.51)	(8.01)	(7.03)
Industry	YES	YES	YES
Year	YES	YES	YES
F-value	5.30	3.29	4.66
Adj R2	0.018	0.018	0.032
N	2793	1482	1311

Note: The t statistic is in parentheses. ***, **, * represent significance at the levels of 1%, 5%, and 10%, respectively.

for the full sample (column 1). The test results show that financial constraints (WW) and corporate environmental irresponsibility (CEIR) were significantly positively correlated, consistent with the main effect H1 result, and thus the positive correlation between financial constraints and corporate environmental irresponsibility is further verified. The results of the property rights grouping test showed that the regression coefficients of the financial constraints and corporate environmental irresponsibility of state-owned enterprises and non-state-owned enterprises were 3.322 (not passing the significance test) and 8.653, respectively, which further verifies that the positive correlation between financial constraints and corporate environmental irresponsibility was significant only for the non-state-owned enterprises. In general, the regression coefficients of WW and WW × boardgender were positive and negative, respectively, and were significant at the 10% level, providing an indication that the gender diversity of executives had a significant weakening effect on the positive correlation between financial constraints and corporate environmental irresponsibility.

Columns 2 and 3 of Table 7 further test the different performance of property rights as they are related to the moderating effect of executive gender diversity. The results showed that in the state-owned enterprise group, the correlation coefficient of the cross-product item (WW × boardgender) was negative (−23.49) and significant at the 10% significance level, indicating that the gender diversity of executives can weaken the adverse impact of financial constraints on corporate environmental irresponsibility. When the degree of financial constraints is high, and the proportion of female executives is also high, the possibility of corporate environmental irresponsibility will be reduced. However, in the non-state-owned enterprises, the correlation coefficient of the WW × boardgender factor was negative (−21.96), but it failed to pass the significance test. This shows that the weakening effect of executive gender diversity played a role only in the state-owned enterprises, and that it did not weaken the rise of corporate environmental irresponsibility caused by the financial constraints of the non-state-owned enterprises. This may be due to the differences in discourse power and political literacy between female executives in state-owned enterprises and those in non-state-owned enterprises.

4.3.2. The Moderating Effect of Regulatory Distance on Corporate Environmental Irresponsibility

We conducted a regression analysis on Model 4 to test whether the gender diversity of executives can moderate the relationship between physical regulatory distance, power regulatory distance, and corporate environmental failure. The test results (

Table 8. Test Results of the Regulatory Effects of Executive Gender Diversity (H3b).

Variable	(1)	(2)	(3)	(4)	(5)	(6)
	Full Sample	State-Owned Enterprise	Non-State Enterprise	Full Sample	State-Owned Enterprise	Non-State Enterprises
Distance1	0.071 ***	0.041	0.077 ***
	(3.28)	(0.72)	(3.37)
Distance2				0.552	−0.052	0.565 *
				(1.54)	(−0.05)	(1.72)
BoardGender	3.808	8.229 *	1.025	6.394	−1.330	46.11 *
	(1.61)	(1.82)	(0.32)	(1.37)	(−0.16)	(1.74)
Distance1 × BoardGender	−0.039 *	−0.305 *	0.009
	(−1.72)	(−1.96)	(0.12)
Distance2 × BoardGender				−0.961 *	−9.162 *	3.133
				(−1.85)	(−1.70)	(0.84)
Lev	−0.117	−1.577	0.861	−0.272	−1.670	0.181
	(−0.09)	(−0.77)	(0.50)	(−0.21)	(−0.81)	(0.10)
ROA	1.886	7.921 **	0.370	1.834	8.012 *	0.226
	(1.10)	(2.24)	(0.19)	(1.07)	(2.25)	(0.12)
Growth	0.019	0.022	−0.017	0.020	0.022	−0.016
	(0.82)	(0.87)	(−0.24)	(0.84)	(0.85)	(−0.23)
Leverage	1.656	4.721 **	0.722	2.003	4.730 **	1.411
	(1.06)	(2.05)	(0.33)	(1.28)	(2.05)	(0.64)
Boardsize	−0.025	−0.034	0.026	−0.017	−0.044	0.023
	(−0.23)	(−0.24)	(0.15)	(−0.16)	(−0.31)	(0.13)
Boardindep	−0.823	2.437	−6.487	−1.165	2.431	−6.649
	(−0.31)	(0.70)	(−1.52)	(−0.44)	(0.70)	(−1.55)
averageage	−0.010	0.063	−0.066	0.007	0.058	−0.041
	(−0.17)	(0.66)	(−0.80)	(0.12)	(0.61)	(−0.50)
OwnCon10	−0.001	0.016	−0.020	−0.003	0.015	−0.022
	(−0.12)	(0.81)	(−1.24)	(−0.28)	(0.79)	(−1.35)
Dual	0.182	0.821 **	−0.322	0.183	0.840 **	−0.321
	(0.66)	(2.06)	(−0.83)	(0.67)	(2.11)	(−0.83)
_cons	23.07 ***	16.56 **	28.54 ***	22.00 ***	17.51 **	30.31 ***
	(6.35)	(2.91)	(5.83)	(5.72)	(2.89)	(6.19)
Industry	YES	YES	YES	YES	YES	YES
Year	YES	YES	YES	YES	YES	YES
F-value	6.60	5.52	7.34	6.59	5.49	7.37
Adj R2	0.070	0.015	0.018	0.060	0.014	0.090
N	2793	1482	1311	2793	1482	1311

Note: The t statistic is in parentheses. ***, **, * represent significance at the levels of 1%, 5%, and 10%, respectively.

) showed that in the full sample, the physical regulatory distance (Distance1) was significantly positively correlated with corporate environmental irresponsibility; the regression coefficient was 0.071 and was significant at the 1% level, which is consistent with the main effect H1 result. In the state-owned and non-state-owned enterprise groups, the regression coefficients of the physical regulatory distance and corporate environmental irresponsibility were 0.041 (not passing the significance test) and 0.077 (significant at the 1% level), which is consistent with the group test results in the main effect. Similarly, in the full sample, power regulatory distance was positively correlated with corporate environmental irresponsibility (the correlation coefficient was 0.552, but the significance test was not passed). In the state-owned and non-state-owned enterprises groups, the correlation coefficients between the regulatory distance (Distance2) and corporate environmental responsibility were, respectively, −0.052 (not passing the significance test), and 0.565 (significant at the 10% level). The results of the group tests were different, because of the difference in the empirical results caused by the gender diversity of executives.

A further test was carried out and the results are shown in Table 8. The regression results showed that in the property rights grouping moderating effect test on the physical regulatory distance (Distance1), the regression coefficient of the crossover term of the state-owned enterprise group was negative (significant at the 10% level). However, the crossover term coefficient of the non-state-owned enterprise was 0.009 (failing to pass the significance test), indicating that the weakening effect of the gender diversity of executives on the physical regulatory distance was only significant for state-owned enterprises. Similarly, in the test of the moderating effect of the property rights grouping on the power regulatory distance (Distance2), the regression coefficient of the crossover term of the state-owned enterprise group was −9.162 (significant at the 10% level). The crossover term coefficient of the non-state-owned enterprise was 3.133 (failing to pass the significance test), showing that the weakening effect of the gender diversity of executives on the power regulatory distance was only significant for the state-owned enterprises, which is consistent with the weakening effect of the physical regulatory distance.

4.4. Further Analysis

To explore whether the mutual effect of financial constraints and the regulatory distance will produce a complementary effect, this paper constructed cross-multiplying items (WW × distance1, WW × distance2), and assessed whether there was a complementary effect or a substitution effect by observing changes in the coefficient of the cross-multiplier, as well as changes in the coefficients of the financial constraints and regulatory distance mentioned above. The test results are shown in

Table 9. Test results of complementary or substitution effect.

Variable	(1)	(2)	(3)	(4)	(5)	(6)
	Full Sample	State-Owned Enterprise	Non-State Enterprises	Full Sample	State-Owned Enterprise	Non-State Enterprises
WW	−0.976	0.213	−1.605	−1.229	3.248	−302.5 **
	(−0.77)	(0.12)	(−0.68)	(−0.63)	(1.05)	(−2.28)
Distance1	0.224 ***	0.0426	0.288 ***
	(3.99)	(0.36)	(4.11)
WW × Distance1	0.221 ***	0.026	0.287 ***
	(4.07)	(0.23)	(4.23)
Distance2				1.206 **	−1.148	65.34 **
				(1.97)	(−0.70)	(2.36)
WW × Distance2				1.133 *	−1.531	61.47 **
				(1.90)	(−0.98)	(2.31)
Lev	−0.723	−3.793 ***	2.356 *	−0.821	−4.115 ***	1.681
	(−0.81)	(−2.92)	(1.83)	(−0.92)	(−3.16)	(1.30)
ROA	1.782	5.658 *	0.411	1.499	5.793 *	−0.210
	(0.99)	(1.70)	(0.19)	(0.83)	(1.73)	(−0.10)
Growth	0.061	0.074	0.101	0.097 **	0.067	0.101
	(1.37)	(1.28)	(1.07)	(2.22)	(1.24)	(1.06)
Leverage	−0.218	2.855 *	−3.141 *	0.008	3.167 **	−2.722
	(−0.19)	(1.94)	(−1.69)	(0.01)	(2.14)	(−1.46)
Boardsize	−0.026	−0.029	−0.061	−0.024	−0.033	−0.079
	(−0.41)	(−0.40)	(−0.50)	(−0.37)	(−0.45)	(−0.64)
Boardindep	1.610	0.345	3.399	1.637	−0.272	3.209
	(0.75)	(0.12)	(0.99)	(0.76)	(−0.10)	(0.94)
averageage	−0.064 *	−0.022	−0.088	−0.042	−0.012	−0.075
	(−1.65)	(−0.34)	(−1.64)	(−1.03)	(−0.19)	(−1.38)
OwnCon10	−0.037 ***	−0.027 ***	−0.046 ***	−0.038 ***	−0.023 **	−0.0485 ***
	(−5.21)	(−2.75)	(−4.43)	(−5.28)	(−2.29)	(−4.62)
Dual	0.529**	−0.073	0.909 ***	0.510 **	−0.014	0.876 ***
	(2.07)	(−0.17)	(2.75)	(1.97)	(−0.03)	(2.65)
_cons	27.83 ***	28.52 ***	27.30 ***	26.30 ***	30.53 ***	−293.1 *
	(12.20)	(7.85)	(6.93)	(9.00)	(6.75)	(−2.12)
Industry	YES	YES	YES	YES	YES	YES
Year	YES	YES	YES	YES	YES	YES
F-value	6.18	3.15	5.68	5.05	3.52	4.57
Adj R2	0.022	0.017	0.041	0.017	0.020	0.032
N	2793	1482	1311	2793	1482	1311

Note: t statistic is in parentheses. ***, **, * represent significant at the level of 1%, 5% and 10% respectively.

. For the entire sample, the coefficients of the cross-product terms (WW × distance1 and WW × distance2) were positive being 0.221 (significant at the 1% level) and 1.133 (significant at the 10% level), respectively. This shows that the comprehensive role of financial constraints and regulatory distance on corporate environmental irresponsibility had a complementary effect; that is, the stronger the financial constraints imposed on the company, and the greater the physical (power) regulatory distance, the more severe the level of corporate environmental irresponsibility. The group test results show that the complementary effect existed only for non-state-owned enterprises.

4.5. Endogenous Control and Robustness Test

To eliminate the endogenous problems that may be caused by the omission of some control variables, considering that the enterprise’s environmental irresponsibility is likely to be affected by its own past level, we drew on the example of Jo and Na (2012) [115] and introduced the lag term of corporate environmental responsibility as the control variable to conduct the regression again. The regression results showed that the corporate environmental irresponsibility in period t-1 was significantly positively correlated with the corporate environmental irresponsibility in period t. The regression results of the other sections were basically consistent with the previous conclusions, indicating that the set model did not have endogenous problems.

To ensure the robustness of the model estimation results, the following robustness tests were conducted: (1) We reduced the sample size. The main effect test (H1 and H2) and the moderating effect test (H3a and H3b) were carried out on the full sample group, the state-owned enterprise group, and the non-state-owned enterprise group of 317 companies in the manufacturing industry. The test results were consistent with the previous conclusions. (2) We used substitution variables, and we used the KZ index instead of the WW index to measure the financial constraints. We then conducted robustness tests on the main effects (H1) and the moderation effects (H3a). The typical methods for the quantitative measurement of financial constraints used by academics in China and internationally are the KZ index, the WW index, and the SA index. The SA index uses only two exogenous variables that do not change greatly over time, namely, the scale of the company and the age of the company. These considerations are not comprehensive. Therefore, to ensure the robustness of the results, the KZ index, which is widely recognized, was used for robustness testing. The KZ index was calculated following the method of Kaplan and Zingales (1997) [116]. As with the WW index, the larger the KZ index, the higher the degree of financial constraints faced by the enterprise. The test results were consistent with the previous conclusions

5. Conclusions

5.1. Empirical Conclusions and Discussion

The study found that corporate financial constraints and environmental irresponsibility were significantly positively correlated, physical regulatory distance was significantly positively correlated with corporate environmental default, but that power regulatory distance failed the significance test. The grouping results show that the positive correlation between financial constraints and corporate environmental failure was more significant in non-state-owned enterprises than in state-owned enterprises, and the positive correlation between the physical regulatory distance and corporate environmental failure was only significant in non-state-owned enterprises. The results show that financial constraints as an enterprise internal cause, was the key factor affecting enterprise environmental decision-making—the lack of available financial resources mitigates against taking environmental responsibility, though state-owned enterprises, due to their special mission and purpose, are obliged to act with greater social responsibility.

The positive correlation between the power regulatory distance and corporate environmental default was only significant in state-owned enterprises. Since state-owned enterprises have strong natural political connections, they more closely reflect the national will, are strongly constrained by national policies, and are effectively obliged to assume due environmental responsibility. Even when state-owned enterprises are located in remote areas, this strong sense of social responsibility also drives their production and business activities to meet the requirements of environmental protection. Non-state-owned enterprises are not so aware of these responsibilities. If, out of opportunism, they breach correct environmental behavior due to their production and business activities, they can rely on money to conceal this. However, when state-owned enterprises operate in a remote area, ecological arguments affect them more strongly. The positive correlation between power regulatory and enterprise environmental negligence was significant only for state-owned enterprises, which may be because in state-owned enterprises the government level distance is more obvious, reflecting county, city, provincial and central government levels. Non-state-owned enterprises are not constrained by power regulatory distance. In sum, it is imperative to solve the problem of enterprise financial constraint from the roots, by enhancing the internal and external financing ability and future profitability of enterprises and strengthening the supervision of enterprise environmental problems. Financial constraints increase the pressure on the enterprise environment, while regulatory distance provides the enterprise with the opportunity to carry out irresponsible behavior, and external pressure and opportunity lead to environmentally irresponsible behavior. Thus, this paper expands the scope for application of the fraud triangle theory.

The gender diversity of enterprise executives plays a significant weakening moderating role on the relationship between the financial constraints of state-owned enterprises and the regulatory distance to government bodies that oversee corporate environmental failure. However, according to the results of further group testing, the gender diversity of executives only weakens the positive correlation between the financial constraints of state-owned enterprises and the regulatory distance; they do not play a weakening role in non-state-owned enterprises. Compared with female executives of non-state-owned enterprises, female executives of state-owned enterprises have a stronger risk perception and can actively detect potential risks when there are signs of financial capital shortage. In addition, due to the special political relevance, state-owned enterprises have more advantages with respect to bank loans and capital support, so they are less likely to be subject to financial constraints than non-state-owned enterprises. However, driven by interests, female executives of non-state-owned enterprises are more likely to invest in projects with high risks, high profits, and quick returns, and pay less attention to corporate environmental responsibility. Female executives in state-owned enterprises are mostly party members. As party members, they pay more attention to corporate society, assume more environmental responsibilities, and show a cautious attitude towards corporate environmental misconduct. In contrast, in non-state-owned enterprises, the proportion of female party members in senior management is relatively low, and most work to ensure that the enterprise is profitable, with career goals of maximizing profits for the enterprise.

5.2. Recommendations and Limitations

This article has confirmed that financial constraints and supervision impact corporate environmental irresponsibility. The condition of financial capital affects the enterprise’s environmental decision-making. Thus, enterprises should strengthen the management of financial funds, and ensure reasonable allocation of funds as far as possible to reduce the financial capital conditions that lead to corporate environmentally irresponsibility behavior. At the same time, we should not leave matters to chance. Since regulatory distance and the high cost of adherence to regulations undermines attention to environmental protection, this can affect the normal production processes of enterprises and cause damage to their reputation. For the government, it is necessary to use the “visible hand” to guide and regulate enterprises to carry out environmental protection practices, pay attention to environmental protection issues, and shoulder due environmental protection obligations. In addition, further research in this paper has demonstrated that gender diversity in senior management encourages more open communication by being more responsive to environmental demands. The dual approach of changing the structure of the existing board of directors and improving regulatory and management ability weakens the positive correlation between financial constraints and regulatory distance on corporate environmental irresponsibility. Therefore, organizations should pay more attention to the environmental protection of enterprises to reduce the possibility of environmental negligence.

There are several limitations to this paper which include: (1) in the actual analysis, we have only considered whether the level of financial constraints will affect environmental irresponsibility, and have not discussed the extent of the impact of financial constraints on corporate environmental irresponsibility. We also have not discussed the different effects of financial constraints on corporate environmental irresponsibility. Future research can divide financial constraints into different levels to explore whether there are differences in the impact of different levels of financial constraints on corporate environmental irresponsibility, and to what extent financial constraints affect the probability of corporate environmental irresponsibility. (2) This paper put forward the concept of environmental irresponsibility for the first time and measured corporate environmental irresponsibility by constructing a scale. It has not considered the nature, severity, or frequency of environmental irresponsibility. Therefore, it is impossible to determine whether the differences in the nature of corporate environmental irresponsibility were affected by financial constraints and regulatory distance. Therefore, future research can start from specific environmental default events, consider the differences in the nature, severity, and frequency for each accounting year, and explore the impact of internal and external factors on corporate environmental irresponsibility from a deeper and more specific perspective.