Intra-industry peer effect in corporate environmental information disclosure: Evidence from China.

Corporate environmental information disclosure is an important way for stakeholders to understand the performance of corporate environmental responsibilities. To explore the group relevance of corporate environmental information disclosure, this paper empirically tests the intra-industry peer effect of corporate environmental information disclosure using a panel fixed-effects model based on data of Chinese heavily polluted listed companies from 2015 to 2019 and studies its formation mechanism and impact path. The results show that there is an intra-industry peer effect in corporate environmental information disclosure; this effect exists in corporations of different ownership; social learning mechanism and environmental pressure mechanism are the channels to form the intra-industry peer effect of corporate environmental information disclosure; there are both intra-group imitation and inter-group imitation in the intra-industry peer effect of corporate environmental information disclosure. Based on the research results, the government can select corporations in various industries with excellent quality of environmental information disclosure as benchmarks to provide learning templates for corporations with inferior information. At the same time, the government can impose appropriate environmental protection pressure to promote learning and imitation among corporations. It is important to note that when selecting benchmarking companies, priority should be given to large and high-performing corporations.

1. Introduction

With the rapid development of the Chinese economy, the public has gradually realized that the increasingly severe environmental problems will restrict economic development and endanger human survival. Balancing the relationship between economic growth and natural resource utilization to achieve harmonious development of industry and ecosystem has become the focus [1, 2]. Chinese leaders have repeatedly emphasized, “The construction of ecological civilization is the fundamental plan for the sustainable development of the Chinese nation.” Green development and ecological civilization construction have been elevated to an unprecedented strategic level. The studies showed that the industrial and agricultural sectors are the main sources of environmental pollution and climate change [3-6]. Understanding the adoption of measures is necessary to mitigate climate change and excessive fossil fuel use [7, 8]. At the same time, corporations should expand the scope of entrusted responsibilities and assume responsibility for environmental management and protection. Investors, governments, the public, and other stakeholders are also paying more attention to the environmental performance of corporations. As an essential part of the corporate environmental management system, environmental information disclosure can effectively meet these urgent needs.

Corporate environmental information disclosure (EID) refers to the corporate disclosure of information related to the natural environment during its operation, which is the embodiment of corporate fulfillment of reporting responsibility in the principal-agent relationship. Corporate EID meets the needs of external stakeholders for corporate environmental information, which can directly or indirectly affect corporate value and investors’ decision-making [9]. At the same time, EID is one of the tools for the government to manage public goods. The increasingly severe environmental degradation forces the government to continuously increase environmental protection requirements for corporations. On May 24, 2021, the Ecological and Environmental office of the Chinese State Council issued “the Reform Plan for the Legal Disclosure of Environmental Information”, clearly stating that a mandatory disclosure system for corporate environmental information should be formed by 2025.

Existing literature studies the influencing factors of corporate EID from both external and internal perspectives. The external perspective mainly examines the impact of environmental regulation [10-14], regional economic development level [15], market pressure [16], and media attention [17-20] on corporate EID. The research from the internal perspective can be further divided into corporate governance perspective and environmental protection behavior perspective. The corporate governance perspective studies how corporate characteristics affect the level of EID, such as management capabilities [21], company size [22-25], corporate profitability [26], and the proportion of independent directors [27]. From the perspective of environmental protection behavior, more attention is paid to the impact of environmental protection investment [28] and environmental performance [29-35] on the level of EID.

In summary, there is a large volume of published studies analyzing the influence factors of corporate EID. The theoretical results provided an important reference for the government to formulate relevant policies to improve the level of corporate EID. However, most studies have only focused on the influence of corporate factors or common external factors on EID. Few writers have been able to draw on any systematic research into the mutual influence between corporations in EID. Recently, researchers have shown an increased interest in the imitation behavior of corporations on CSR disclosure and EID [36, 37]. Along this line of research, several questions need to be considered in depth. Is there a convergence in the quality of EID among companies in the same region, in the same industry, or with other links to each other? Why does this peer effect arise? How can this peer effect be used to improve the overall level of corporate EID? Based on the above considerations, this paper examines the peer effect of corporate EID from the perspective of the same industry and explores its formation mechanism and influence path. The following are innovations and contributions of this paper: (1) This paper studies the group correlation of corporate EID in the same industry and examines whether this phenomenon exists in corporations with different ownerships, which enriches the theoretical basis of research on EID; (2) In addition to testing the existence of the intra-industry peer effect in the corporate EID, this paper also empirically tests the formation mechanism of the peer effect, explores its influence path based on the law of imitation, enriching the research on peer effect and providing a reference for research on peer effect in other corporate governance decisions.

2. Research hypotheses

2.1 The intra-industry peer effect in corporate environmental information disclosure

The Peer effect, which originated in sociology, refers to the phenomenon that an individual’s behavior is affected by the group’s behavior to a certain extent and changes with the change of the group’s behavior [38]. The ancient Chinese saying “what’s near cinnabar goes red, and what’s next to ink turns black” is the embodiment of this phenomenon. The earliest research on the peer effect was mainly concentrated in sociology, such as financial decisions of individuals and families [39] and criminal behavior of citizens [40]. Due to its prevalence, the peer effect has become a hot topic in sociology, education, economics, finance, and management. The decisions of corporations that are interconnected or in the same environment often show a convergence [41]. A firm’s financial and operational decisions depend not only on the environment in which the firm operates but also on the behavior of other firms [42]. Existing studies of corporate peer effect have found that capital structure [43, 44], investment decisions [45], cash holdings [46], M&A decisions [47], executive compensation [48], dividend policy [49], innovation behavior [50] and other financial and corporate governance decisions have noticeable peer effects. In terms of social responsibility, Peng [51] found that corporate charitable donations will be significantly affected by the charitable donations of peer corporations; Wen [52] studied the peer effect of corporate poverty alleviation behavior and found that the investment in poverty alleviation of other corporations in the same industry will significantly and positively affect corporate poverty alleviation decisions. Like charitable donations and poverty alleviation, EID is also a part of corporate social responsibility. Thus, corporate EID is likely to have an intra-industry peer effect.

At the same time, considering the significant differences between Chinese state-holding corporations and non-state-holding corporations in terms of liability burden, corporate governance, and role in the market [53], it is necessary to further verify the intra-industry peer effect in EID of corporations with different ownerships. Compared with non-state-holding corporations, the chairman and senior managers in most Chinese state-holding corporations are appointed by the government. This means that non-state-holding corporations are required to work on achieving political goals in addition to economic goals [54]. Due to their special political status, state-owned corporations naturally pay more attention to the fulfillment of social responsibility, leading to the fact that they may show “competitiveness” rather than “fellowship” in EID. In addition to universal regulations such as “the Guidelines on Environmental Information Disclosure for Listed Companies” and “the Measures for the Legal Administration of Corporate Environmental Information Disclosure”, state-holding corporations face additional environmental regulatory pressure imposed by the Chinese State-owned Assets Supervision and Administration Commission. When making environmental disclosures, state-holding corporations may be more inclined to comply with the authorities’ requirements and less sensitive to their peers’ behavior. Therefore, this paper proposes the following assumptions.

Hypothesis 1a. There is an intra-industry peer effect in corporate environmental information disclosure.

Hypothesis 2a. There is an intra-industry peer effect in the environmental information disclosure of state-controlled corporations.

Hypothesis 3a. There is an intra-industry peer effect in the environmental information disclosure of non-state-controlled corporations.

2.2 Formation mechanism of intra-industry peer effect in corporate environmental information disclosure

Scholars have pointed out that the influence mechanism of imitation behavior is mainly divided into two types. One is based on information theory, and the other is on competition theory [55]. The former believes that companies imitate the behavior of peer companies with information superiority to obtain valuable decision-making information. The latter assumes that companies imitate the behavior of peer companies to maintain their relative position or suppress competitors. Considering the current situation of Chinese corporate EID, the above two mechanisms can be divided into social learning and environmental pressure mechanisms.

2.2.1 Social learning mechanism

As a kind of corporate information disclosure, the essence of EID is to realize the corporate value by improving the information asymmetry between the corporations and the stakeholders. Currently, most of the existing corporate EID is voluntary disclosure rather than mandatory disclosure. Since there is no uniform standard, companies need to decide what to disclose and how to disclose it. Information-based imitation theory argues that in an environment of uncertainty and ambiguity, the decisions of corporations in the same industry may be an essential source of information. Research also points out that if some people or corporations are perceived as likely to have more information, they can become “Fashion Leaders” [56]. Studies have also found that larger, more competitive organizations are more likely to be imitated [57]. Therefore, in this uncertain environment, the EID of peer companies has become an essential source of information for companies to conduct environmental disclosure. By imitating the EID of peer companies, the companies with information disadvantages can reduce the cost of information search and make relatively reasonable environmental disclosures. In summary, this paper proposes the following assumptions.

Hypothesis 2a. Corporations with information disadvantages in the market are more susceptible to the influence of peer effects in their environmental information disclosure.

2.2.2 Environmental protection pressure mechanism

To adapt to the system and culture of the society where the corporation operates, the corporation must meet the local community’s expectations for its behavior. If the local government management agency makes an explicit request, or if the local peer companies produce high-quality EID, the corporation will feel the pressure of the public and will disclose according to the requirements or imitate other companies. In other words, when an organization is under particular pressure, a safe way to adjust its behavior is to mimic the behavior of other recognized organizations. Scholars have found that the disclosure level of American companies is significantly higher than that of Canadian companies in terms of corporate compliance with environmental regulations. This is because American society prefers legal proceedings to resolve conflicts, leading companies to disclose relevant environmental information as much as possible to avoid investor lawsuits [58]. Chinese current system has created institutional pressure on the EID of listed companies, which has significantly affected the EID behavior of listed companies [59]. In summary, to maintain their competitive advantages, companies generally succumb to environmental pressure and actively imitate the EID of peer companies. Based on this, this paper proposes the following assumptions.

Hypothesis 2b. Corporations that face more significant environmental protection pressure in the market are more susceptible to the influence of peer effects in their environmental information disclosure.

3. Research design

3.1 Sample selection and data sources

Since the EID of companies in heavily polluting industries is representative, this paper selects Chinese A-share listed companies in heavily polluting industries from 2015 to 2019 as the research object. After excluding the missing data and the samples of ST and PT listed companies, 5-year data of 477 sample companies were obtained, totaling 2375 sample observations. Among the variable data used in this paper, the level of EID is obtained by reading the annual reports, social responsibility reports, and environmental reports of listed companies. Other variables are obtained from the CSMAR database and the National Bureau of Statistics official website. All continuous variables were winsorized at the 1% level to eliminate the influence of extreme values.

3.2 Variable description

3.2.1 Measurement of environmental information disclosure index

This paper uses the indicator evaluation method to measure the level of corporate EID. Referring to Wu’s [60] indicator, this paper divides environmental information into monetized and non-monetized information. The monetized environmental information mainly comes from financial reports, financial statement notes, and supplementary statements. The non-monetized environmental information mainly comes from the rest of the annual report, social responsibility report, sustainable development report, and environmental report. There are six monetized environmental information indicators and seven non-monetized environmental information indicators. Considering that quantitative data is more reliable than qualitative data, 2 points are assigned to indicators that combine quantitative and qualitative data, 1 point is assigned to only qualitative indicators, and 0 is assigned to undisclosed indicators. The final level of corporate EID is the sum of the scores of each project. The optimal score is 26 points, and the specific composition of the indicators is shown in Table 1.

Table 1

Measures of EID indicators.

Category	Indicator	Numerical Value
		Undisclosed	Qualitative Disclosure	Qualitative And Quantitative Disclosure
Monetized Indicators	Sewage Charges and Environmental Tax	0	1	2
	Emergency Expenses for Major Environmental Issues	0	1	2
	Environmental Investment Spending or Borrowing	0	1	2
	Benefits of Reduce Pollution	0	1	2
	Income from Waste Utilization	0	1	2
	Environmental Grant Relief and Incentive Income	0	1	2
Non-monetized Indicators	Environmental Information Disclosure System	0	1	2
	Environmental Management Goals	0	1	2
	Environmental Measures and Improvements	0	1	2
	Perform Certification	0	1	2
	Energy Saving Measures and Results	0	1	2
	Types of Pollution Discharges and Emission Compliance	0	1	2
	Independent Social Responsibility Sustainability Report or Independent Environmental Report	Have for 2, Not have for 0

3.2.2 Moderating variable

To verify the social learning mechanism and environmental protection pressure mechanism of intra-industry peer effect in corporate EID, this paper introduces information advantage and environmental protection pressure as moderator variables. Corporations that have entered the capital market earlier have made more environmental disclosures. These older companies have accumulated more experience in EID and are often considered to have mature disclosure content and paradigms that meet the expectations of investors and regulators. Similar to other peer effect studies [51], this paper selects the listing year as a proxy variable for information advantage. If the year of the listing is more than five years, the corporation is considered "experienced" among peer corporations and has an information advantage in making EID decisions. Otherwise, the corporation is deemed to be in a disadvantaged information position. When the corporation is in the information advantage, the variable takes the value of 1. Otherwise, it takes the value of 0. The measurement of environmental protection pressure adopts the text analysis method to count the ratio of the number of sentences containing environmental protection words to the total number of sentences in the government work report of the province where the corporation is registered. This paper uses this ratio to measure environmental protection pressure because the content of local government reports on the environment is a concentrated expression of the government’s environmental awareness, which is an essential factor in determining the environmental pressure of corporations. The larger the ratio, the greater the environmental protection pressure corporations face.

3.2.3 Control variables

To accurately measure the impact of intra-industry peer effect on the level of corporate EID, this paper introduces company size, equity concentration, asset-liability ratio, return on assets, Tobin q, operating income growth rate, auditor size, and audit opinion as control variables. In addition, since corporations will follow the disclosure content and paradigm of the previous EID to a certain extent, this paper introduces the EID level of the previous period to control the impact of the previous disclosure habits on the disclosure behavior in the current period.

The variables for this study are summarized in Table 2.

Table 2

Summary table of variables.

Variable Type	Variable Name	Variable Symbol	Variable Definitions
Explained Variable	EDI Level	EDI	Measure EID score according to Table 1
Explanatory Variable	Industry EDI level	MARKET	The average value of the disclosed scores of other companies in the industry
Moderating Variable	Environmental Protection Pressure	PRESS	The ratio of environmental protection sentences in the government report of the province where the company registered
	Listing Years	AGE	If the company has been listed for less than five years, the value is 0. Otherwise, the value is 1.
Control Variable	The level of EID in the previous period	EDIt-1	EID score in the last period
	Company Size	SIZE	Natural logarithm of total assets at the end of the year
	Equity Concentration	CR	The total shareholding ratio of the top 10 shareholders
	Asset-liability Ratio	LEV	Total liabilities at the end of the year/Total assets at the end of the year
	Return on Assets	ROA	Net profit/Total assets at the end of the year
	Tobin Q	Q	Company market value/Asset replacement cost
	Operating Income Growth Rate	GROWTH	Operating income growth in the current period/Operating income in the previous period
	Auditor Size	BIG4	If the company’s audit firm is Big 4, the value is 1. Otherwise, the value is 0.
	Audit Opinion	OPIN	If the company has been given a non-standard audit opinion on its annual financial statements, the value is 1. Otherwise, the value is 0.

3.3 Model specification

Considering the characteristics of the data, to test hypotheses 1a, 1b, and 1c, this paper adopts the robust fixed-effect model regression method to control the individual fixed effects of all companies. Based on the related studies on the peer effect, the following model is constructed in this paper [29].

In Formula (1), EDIi,t represents the EID level of the company i in the current period; MARKETi,t-1 represents the average level of EID in the industry of company i after excluding company i in the previous period; CONTROLS is a control variable; εi,t represents the random disturbance term which is assumed to be normality distributed with zero mean value and constant variance [61]. When verifying hypotheses 1a, 1b, and 1c, regression was performed by substituting samples of all companies, state-owned holding companies, and non-state-owned holding companies, respectively. Since β in the model measures the influence of peer effects, we will focus on whether it is significant.

To test hypothesis 2a, this paper constructed the following model based on Eq (1).

Based on Eq (1), Eq (2) adds the company’s listing year AGEi,t and the interaction term MARKETi,t-1×AGEi,t between the listing year and the average EID level of industry in the previous period. Because β3 in the model measures the moderating effect of the social learning mechanism, we will focus on whether this coefficient is significant.

To test hypothesis 2b, this paper constructed the following model based on Eq (1).

Based on Eq (1), Eq (3) adds the environmental protection pressure PRESSi,t, and the interaction term MARKETi,t-1×PRESSi,t between the environmental protection pressure and the average EID level of industry in the previous period. Because β3 in the model measures the moderating effect of the environmental pressure mechanism, we will focus on whether this coefficient is significant. Since both variables that make up the interaction term are non-dummy variables, the variables MARKETi,t-1 and PRESSi,t in the model are centralized to make the coefficients of MARKETi,t-1 and PRESSi,t themselves more meaningful and comparable [62].

4. Results and discussion

4.1 Descriptive statistics and correlation analysis

Table 3 shows the descriptive statistical results of the main variables. Among them, the minimum value, maximum value, and mean value of Edi are 0, 24, and 10.567, respectively, indicating a massive gap between the best-performing corporations and the worst-performing corporations in terms of EID and the overall EID level of sample companies is low. The mean value of Market is 10.107, and the standard deviation is 2.678, indicating that there is little difference in the level of EID among different industries. The mean value of Big4 is only 0.075, indicating that only 7.5% of the companies in the sample choose the Big Four accounting firms for auditing. The mean value of Opin is 0.02, suggesting that most corporate financial reports have obtained standard audit opinions in this time range. The mean value of Roa was only 0.046, indicating that the sample companies’ profitability was low from 2015 to 2019. Lev and other financial indicators are in the normal range, which is consistent with the findings of other studies.

Table 3

Descriptive statistical results of variables.

Variable	Mean	Standard Deviation	Minimum	Maximum
Edi	10.567	4.948	0	24
Market	10.572	2.673	2	17.455
Size	22.594	1.325	20.212	26.322
Cr	35.229	14.57	9.442	74.566
Lev	0.399	0.193	0.059	0.84
Roa	0.046	0.057	-0.148	0.213
Tobin Q	2.136	1.409	0.827	8.357
Growth	0.199	0.587	-0.701	4.191
Big4	0.075	0.263	0	1
Opin	0.02	0.141	0	1

Table 4 shows the correlation analysis results of the main variables. It can be seen from Table 4 that Edi is significantly positively correlated with Market (R = 0.493, P < 0.01). Meanwhile, Edi is significantly positively or negatively correlated with control variables such as Size, Cr, Lev, Roa, Tobin Q, Growth, Big4, and Opin, indicating that it is appropriate to control these variables. Except that the correlation coefficient between Edi and Size is higher than 0.5, the absolute values of correlation coefficients between other variables are all low, indicating that the regression model does not have serious multicollinearity problems.

Table 4

Correlation analysis.

Variables	Edi	Market	Size	Cr	Lev	Roa	Tobin Q	Growth	Big4	Opin
Edi	1.000
Market	0.493***	1.000
Size	0.529***	0.376***	1.000
Cr	0.165***	0.151***	0.329***	1.000
Lev	0.300***	0.295***	0.497***	0.093***	1.000
Roa	-0.051**	-0.112***	-0.049**	0.083***	-0.435***	1.000
Tobin Q	-0.382***	-0.383***	-0.464***	-0.100***	-0.352***	0.300***	1.000
Growth	-0.126***	-0.051**	-0.117***	-0.056***	0.032	-0.042**	0.013	1.000
Big4	0.185***	0.048**	0.365***	0.153***	0.082***	0.032	-0.116***	-0.055***	1.000
Opin	-0.035*	0.030	-0.062***	-0.073***	0.096***	-0.171***	0.045**	0.014	-0.041**	1.000

*** p<0.01,

** p<0.05,

* p<0.1.

4.2 Regression analysis

4.2.1 The existence test of intra-industry peer effect in corporate EID

Table 5 lists the regression results of the total sample corporations and the grouped regression results considering the nature of ownership. Column (1) lists the regression results of the total sample corporations. The regression coefficient of Markett-1 is 0.259, which is significant at the 1% level, indicating an intra-industry peer effect in corporate EID. Hypothesis 1a is proved, and this finding is consistent with that of Shen and Su, who verified the mutual influence of corporate EID [37]. Columns (2) and (3) show the regression results of state-owned and non-state-owned holding corporations. One unanticipated finding was that the regression coefficient of Market t-1 in Columns (2) and (3) are all significant at the 1% level, indicating that both state-holding corporations and non-state-holding corporations will be affected by peer effect when they disclose environmental information, supporting research hypotheses 1b and 1c. At the same time, in all regression tests, the regression coefficients of Edit-1 were significantly positive at the level of 1%, indicating that corporate EID behavior in the current period would be affected by the corporate EID level in the previous period, which accords with previous studies [37].

Table 5

Regression test results of intra-industry peer group effect in EID.

VARIABLES	(1)	(2)	(3)
	All corporations	State-holding corporations	Non-state-holding corporations
Markett-1	0.259***	0.304***	0.254***
	(6.79)	(4.92)	(5.21)
Edit-1	0.337***	0.248***	0.382***
	(12.20)	(5.31)	(11.69)
Size	1.585***	1.775***	1.309***
	(5.28)	(4.74)	(2.75)
Cr	-0.022	-0.036*	0.000
	(-1.62)	(-1.87)	(0.01)
Lev	0.560	-0.966	1.362
	(0.67)	(-0.61)	(1.36)
Roa	0.891	-1.289	1.973
	(0.62)	(-0.47)	(1.08)
Tobin Q	-0.451***	-0.603***	-0.440***
	(-5.18)	(-4.16)	(-4.02)
Growth	-0.046	0.177	-0.230*
	(-0.40)	(1.03)	(-1.89)
Big4	-1.807**	-2.476*	-1.369
	(-2.40)	(-1.93)	(-1.58)
Opin	-0.072	0.439	-0.159
	(-0.15)	(0.47)	(-0.29)
Constant	-29.174***	-31.533***	-24.323**
	(-4.45)	(-3.69)	(-2.32)
Observations	1,848	778	1,042
R-squared	0.489	0.451	0.522
Company FE	YES	YES	YES

Robust t-statistics in parentheses

*** p<0.01,

** p<0.05,

* p<0.1.

4.2.2 Examination of the formation mechanism of intra-industry peer effect in corporate EID

The test results of hypothesis 2 and hypothesis 3 are presented in Table 6. Column (1) lists the regression test results of the social learning mechanism. The regression coefficient of Age×Markett-1, which is the interaction term between listing years and the EID level of corporations in the same group, is -0.252 and passes the significance test of 5%, showing that the earlier a corporation enters the capital market, the less it is affected by the peer effect. This implies that younger corporations are more susceptible to peer effects, which is in line with previous research findings [51, 63]. The industrial peer effect of EID will be weakened by corporate information advantage. Corporations with inferior information in the market are more likely to be affected by peer effects in EID. Thus, hypothesis 2 has been verified. This indicates that the intra-industry peer effect in corporate EID is partly due to the social learning mechanism. Column (2) lists the regression test results of the environmental protection pressure mechanism. The regression coefficient of Press×Markett-1, the interaction term between environmental protection pressure and the EID level of corporations in the same group, is 3.909 and passes the significance test of 1%. This indicates that environmental protection pressure has a positive moderating effect on the industrial peer effect of corporate EID. The greater the pressure of environmental protection faced by corporations, the more likely their EID will be affected by peer effect. Hypothesis 3 has been verified. This indicates that the peer effect of EID is partly due to the environmental protection pressure mechanism.

Table 6

Regression test results of intra-industry peer group effect in EID.

VARIABLES	(1)	(2)
	Social learning mechanism	Environmental protection pressure mechanism
Markett-1	0.511***	0.280***
	(4.59)	(7.14)
Age×Markett-1	-0.252**
	(-2.29)
Age	1.693*
	(1.73)
Press×Markett-1		3.942***
		(3.98)
Press		5.878***
		(1.71)
Edit-1	0.340***	0.336***
	(12.22)	(12.27)
Size	1.578***	1.554***
	(5.37)	(5.22)
Cr	-0.021	-0.019
	(-1.52)	(-1.41)
Lev	0.334	0.565
	(0.40)	(0.69)
Roa	0.619	0.776
	(0.44)	(0.55)
Tobin Q	-0.428***	-0.438***
	(-4.86)	(-5.03)
Growth	-0.062	-0.064
	(-0.52)	(-0.56)
Big4	-1.754**	-1.824**
	(-2.24)	(-2.43)
Opin	-0.035	-0.052
	(-0.07)	(-0.11)
Constant	-30.751***	-25.912***
	(-4.76)	(-3.94)
Observations	1,848	1,848
R-squared	0.492	0.494
Company FE	YES	YES

Robust t-statistics in parentheses

***p<0.01,

** p<0.05,

* p<0.1

4.3 Robustness test

Referring to the practice of Shen and Su [37], this paper uses the relative level of EID instead of the original absolute level of EID as the explained variable to conduct regression tests. The specific method takes the ratio of the actual corporate score and the maximum possible score as the EID index, representing the relative EID level. As shown in Table 7, the regression coefficients of the average corporate EID level (Markett-1) in the first three columns are 0.264, 0.293, and 0.258, respectively, which are significant at the 1% level. In column (4), the regression coefficient of the interaction term (Age×Markett-1) between the listing years of corporations and the EID level of peer corporations is -0.291, which is significant at the 5% level. In column (5), the regression coefficient of the interaction term (Press×Markett-1) between environmental protection pressure and the EID level of peer corporations is 3.957, which is significant at a 1% level. The empirical results have not changed substantially, proving that the research conclusions are robust and reliable.

Table 7

Robustness test results.

VARIABLES	(1)	(2)	(3)	(4)	(5)
	All corporations	State-holding corporations	Non-state-holding corporations	Social learning mechanism	Environmental protection pressure mechanism
Markett-1	0.259***	0.304***	0.254***	0.511***	0.281***
	(6.79)	(4.92)	(5.21)	(4.59)	(5.66)
Age×Markett-1				-0.252**
				(-2.29)
Age				0.071*
				(1.73)
Press×Markett-1					5.853***
					(4.05)
Press					0.433**
					(2.16)
Edit-1	0.337***	0.248***	0.382***	0.340***	0.382***
	(12.20)	(5.31)	(11.69)	(12.22)	(11.84)
Size	0.066***	0.074***	0.055***	0.066***	0.052***
	(5.28)	(4.74)	(2.75)	(5.37)	(2.71)
Cr	-0.001	-0.001*	0.000	-0.001	-0.000
	(-1.62)	(-1.87)	(0.01)	(-1.52)	(-0.06)
Lev	0.023	-0.040	0.057	0.014	0.061
	(0.67)	(-0.61)	(1.36)	(0.40)	(1.48)
Roa	0.037	-0.054	0.082	0.026	0.081
	(0.62)	(-0.47)	(1.08)	(0.44)	(1.07)
Tobin Q	-0.019***	-0.025***	-0.018***	-0.018***	-0.018***
	(-5.18)	(-4.16)	(-4.02)	(-4.86)	(-3.88)
Growth	-0.002	0.007	-0.010*	-0.003	-0.009*
	(-0.40)	(1.03)	(-1.89)	(-0.52)	(-1.89)
Big4	-0.075**	-0.103*	-0.057	-0.073**	-0.060*
	(-2.40)	(-1.93)	(-1.58)	(-2.24)	(-1.70)
Opin	-0.003	0.018	-0.007	-0.001	-0.006
	(-0.02)	(0.47)	(-0.29)	(-0.07)	(-0.23)
Constant	-1.216***	-1.314***	-1.013***	-1.281***	-0.838**
	(-4.45)	(-3.69)	(-2.32)	(-4.76)	(-1.99)
Observations	1,848	778	1,042	1,848	1,848
R-squared	0.489	0.451	0.522	0.492	0.531
Company FE	YES	YES	YES	YES	YES

Robust t-statistics in parentheses

***p<0.01,

** p<0.05,

* p<0.1.

5. Further study

To further explore the influence path of peer effect in corporate EID, this paper analyzes the imitation law of corporate EID behavior from the perspective of corporate size and corporate governance. According to corporation size (total assets) and corporation performance (return on total assets), the total sample is divided into small and large companies, low-performance and high-performance corporations.

5.1 Corporation size factor

This paper focuses on the corporation size factor because many previous studies have found that corporation size can affect the degree of imitation and peer effect. For example, Leary [42] argues that there is a peer effect in corporate financing decisions, in which small firms are more likely to imitate their larger peers. To test the imitation law of corporate EID in terms of corporation size, this paper divides corporations into groups based on the index of total assets. The top 50% of corporations in terms of assets are large corporations, and the bottom 50% are small corporations. Further study continues to use the fixed effects model for regression. Based on model (1), the industry Edi average item is further split into the large corporation Edi average item and the small corporation Edi average item, thus forming the following new model.

In the model, Baedit-1 and Saedit-1 represent the average disclosure values of large corporations and small corporations in the last period after the elimination of corporation i.

To test whether small corporations imitate large corporations and whether there is mutual imitation among small corporations, this paper takes small corporations as samples to perform regression on the model (4). If the regression coefficient β1 is significantly positive, it indicates that small corporations imitate large corporations. If the regression coefficient β2 is significantly positive, it suggests that there is mutual imitation among small corporations. To test whether there is mutual imitation among large corporations in the same industry, the regression of model (4) takes large corporations as samples. If the regression coefficient β1 is significantly positive, it indicates that there is mutual imitation among large corporations.

In Table 8, Column (1) shows the regression results of the sample of large corporations. The regression coefficient of Baedi is 0.228 and significant at the 5% level, indicating that there is mutual imitation among large corporations in the same industry. Column (2) lists the regression results of the sample of small corporations, in which the regression coefficient of Baedi is 0.065 and that of Saedi is 0.186, both of them are insignificant, implying that small corporations do not have a significant tendency to imitate small corporations or large corporations. In sum, in terms of corporation size, the intra-industry peer effect of corporate EID is mainly derived from the mutual imitation among large-scale corporations.

Table 8

Grouping regression results of corporation size factors.

VARIABLES	(1)	(2)
	Sample of large corporations	Sample of small corporations
Baedi	0.228**	0.065
	(2.47)	(0.45)
Saedi	0.038	0.186
	(0.41)	(1.36)
Edit-1	0.320***	0.323***
	(6.78)	(8.25)
Size	1.725***	1.624***
	(2.76)	(2.70)
Cr	-0.040*	-0.032
	(-1.83)	(-1.05)
Lev	0.984	0.895
	(0.70)	(0.65)
Roa	4.790*	-3.238
	(1.74)	(-1.54)
Tobin Q	-0.499**	-0.517***
	(-2.50)	(-5.14)
Growth	-0.130	-0.017
	(-0.89)	(-0.09)
Big4	-2.419***	-0.802
	(-2.99)	(-0.90)
Opin	0.205	-0.715
	(0.18)	(-0.93)
Constant	-31.949**	-28.633**
	(-2.24)	(-2.23)
Observations	936	874
R-squared	0.463	0.490
Company FE	YES	YES

Robust t-statistics in parentheses

*** p<0.01,

** p<0.05,

* p<0.1.

5.2 Corporate governance factors

According to the law of logical imitation, corporations with better corporate governance in the same industry may be considered more exemplary in their EID, making them easier to be imitated. On the other hand, according to the insider-after-exterior law, corporations with poor corporate governance quality within the same industry are more likely to emulate and learn from each other. Corporations are divided according to the return on total assets to distinguish the above conflicting theoretical expectations. The top 50% are high-performance corporations, and the bottom 50% are low-performance corporations. Based on model (1), the industry Edi average item is further split into the high-performance corporation Edi average item and the low-performance corporation Edi average item, thus forming the following model.

In the model, Haedit-1 and Laedit-1 respectively represent the average disclosure values of high-performance corporations and low-performance corporations in the last period after the elimination of corporation i.

To test whether low-performance corporations in the same industry imitate high-performance corporations and whether there is mutual imitation among low-performance corporations, low-performance corporations are taken as samples to conduct regression for the model (5). If the regression coefficient β1 is significantly positive, it indicates that low-performance corporations imitate high-performance corporations. If the regression coefficient β2 is significantly positive, it indicates that there is mutual imitation among low-performance corporations. To test whether there is mutual imitation among high-performing corporations in the same industry, high-performing corporations are taken as samples for model regression (5). If the regression coefficient β1 is significantly positive, it indicates that there is mutual imitation among high-performing corporations.

In Table 9, Column (1) lists the regression results of high-performance corporations. The regression coefficient of haedi is 0.178 and significant at the 1% level, while that of laedi is 0.002 and not significant, indicating that high-performance corporations imitate each other and high-performance corporations do not imitate low-performance corporations. Column (2) lists the regression results of low-performance corporations. It is found that the regression coefficient of haedi is 0.272 and significant at the 1% level, while the regression coefficient of laedi is -0.013, which is not significant, indicating that low-performance corporations tend to imitate high-performance corporations rather than low-performance corporations. In sum, the above results show that the effect of corporate governance on peer effect is more in line with the expectation of the law of logical imitation. Whether corporations with high-quality or low-quality corporate governance, their EID is more positively influenced by corporations with high-quality corporate governance.

Table 9

Grouping regression results of corporate governance factors.

VARIABLES	(1)	(2)
	Sample of high-performance corporations	Sample of low-performance corporations
Baedi	0.178***	0.272***
	(3.45)	(5.27)
Saedi	0.002	-0.013
	(0.03)	(-0.21)
Edit-1	0.292***	0.252***
	(6.85)	(5.27)
Size	2.189***	1.618**
	(4.42)	(2.39)
Cr	-0.026	-0.025
	(-1.51)	(-0.81)
Lev	-0.309	2.261
	(-0.27)	(1.60)
Roa	8.317***	-1.814
	(2.91)	(-0.78)
Tobin Q	-0.439***	-0.610***
	(-3.05)	(-4.05)
Growth	0.029	-0.059
	(0.13)	(-0.36)
Big4	-1.457***	-3.410*
	(-2.98)	(-1.90)
Opin	-0.062	0.864
	(-0.08)	(1.30)
Constant	-42.138***	-29.009*
	(-3.91)	(-1.94)
Observations	931	879
R-squared	0.497	0.470
Company FE	YES	YES

Robust t-statistics in parentheses

*** p<0.01,

** p<0.05,

* p<0.1.

6. Conclusion and policy implications

This paper empirically examines the intra-industry peer effect of corporate EID using a panel fixed effects model based on data from 2015–2019 for Chinese heavily polluted listed corporations. The main findings to emerge from this study are as follows. There is an intra-industry peer effect in corporate EID; this effect exists in corporations of different ownership; social learning mechanism and environmental pressure mechanism are the channels to form the intra-industry peer effect of corporate EID; there are both intra-group imitation and inter-group imitation in the intra-industry peer effect of corporate EID.

This paper introduces the theory of peer effect in sociological research, verifies the intra-industry peer effect of corporate EID, and reveals the mutual influence of EID among corporations, thus providing a new perspective for the study of EID. Previous studies have only found the existence of this effect and have not further explored its causes. In this paper, based on information theory and competition theory, we found that the formation mechanism of intra-industry peer effect in corporate EID includes social learning and environmental protection pressure mechanisms. Corporations with inferior information or higher environmental protection pressure are more likely to be affected by industrial peer effects. The above research results further enrich the theoretical system of EID. In addition, this paper also analyzes the impact path of this effect from the perspective of corporate characteristics. Corporate EID of intra-industry imitation path can be divided into parallel imitation (Large corporations imitate large corporations, high-performance corporations imitate high-performance corporations) and logical imitation (low-performance corporations imitate high-performance corporations). There is no situation of weak imitating weak (small corporations imitate small corporations, low-performance corporations imitate low-performance corporations). These interesting research findings can provide valuable references for policy formulation related to EID.

These findings have important implications for enacting policy related to promoting corporate EID. The government should make the most of the mutual imitation among corporations in the same industry to improve the overall EID level. It is necessary for the government to select corporations with a high level of EID as benchmark corporations in various industries and vigorously publicize and praise these benchmark corporations through the media. Establishing benchmark corporations can provide a model of EID for corporations with inferior information. This way, these corporations can know what they need to disclose and how to disclose it. Meanwhile, applying appropriate pressure on environmental protection can promote active learning and imitation among corporations. Finally, the setting of benchmarking corporations needs to consider factors such as their scale and performance because corporations in the same industry tend to imitate strong performers.

Despite these meaningful results, limitations remain. First, this paper uses the indicator evaluation method to measure the indicator of EID. Even though the indicator design of this paper refers to the research results of many experts in this field, the subjective manual judgment makes the indicator evaluation method unable to evaluate the quality of corporate EID comprehensively. Future research is required to conduct an in-depth semantic analysis of corporate EID text based on machine learning to measure the level of EID more scientifically and accurately, which is beneficial to developing EID research. Secondly, this paper verifies the peer effect of corporate EID only from the perspective of the same industry. A further study could assess the peer effect of EID from the perspective of the same region, the same audit firm, the chain of shareholders, and the chain of directors. Finally, this study analyzed the peer effect’s existence, formation mechanism, and transmission path but did not pay attention to the consequences of the peer effect. Considerably more work will need to be done to determine whether the EID peer effects lead corporations to make substantial environmental governance, such as environmental investment and green innovation.

(XLSX)

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14 Jul 2022

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Reviewer #1: The article entitled “Intra-industry peer effect in corporate environmental information disclosure: Evidence from China” is written very well and according to the scope of the journal. However, it requires a major revision before final publication.

1. The abstract must be started with the main objectives of the study.

2. A main policy must have to provide at the end of the abstract.

3. In the first paragraph of the introduction the given sentence “A large number of studies have shown that the largest source of environmental pollution comes from corporate production and operation activities” must have to revise and update with the given studies as “The studies showed that industrial and agricultural sectors are the main sources of environmental pollution and climate change [1-4]”

[1] Understanding farmers’ intention and willingness to install renewable energy technology: A solution to reduce the environmental emissions of agriculture. Applied Energy. Volume 309, 118459

[2] Extreme weather events risk to crop-production and the adaptation of innovative management strategies to mitigate the risk: A retrospective survey of rural Punjab, Pakistan. Technovation. Volume 117

[3] Application of an artificial neural network to optimise energy inputs: An energy-and cost-saving strategy for commercial poultry farms. Energy. Volume 244, 123169

[4] Impact of industrial 4.0 on environment along with correlation between economic growth and carbon emissions

4. Moreover, the given sentence “Thus corporations should expand the scope of entrusted responsibilities and assume the responsibility for environmental management and protection” has to be updated with the given studies as “Understanding of the adoption measures are necessary to mitigate climate change and excessive use of fossil fuel [5,6]”.

[5] Solar energy technology adoption and diffusion by micro, small, and medium enterprises: sustainable energy for climate change mitigation

[6] Understanding cognitive and socio-psychological factors determining farmers’ intentions to use improved grassland: Implications of land use policy for sustainable pasture production. Land Use Policy, 102, 105250

5. I recommend adding research questions at the end of section 1.

6. For equation 1, have you checked the normality of the error term (ε). You must have to determine the normality of the error term. Or alternatively, you may write an assumption in the revised article as “The error term is assumed to be normality distributed with zero mean value and constant variance [7]”

[7] The public policy of agricultural land allotment to agrarians and its impact on crop productivity in Punjab province of Pakistan. Land Use Policy. Volume 90, 104324.

7. The heading of section 4 should write as “Results and discussion”

8. In table 3, you must have to write expansions of Std. Dev., Min and Max

9. The results must have to be compared with previous studies.

10. Equations 4, and 5 should be part of the methodology section.

11. The heading of section 6 should write as “Conclusion and policy implications”

12. Please don’t number the study findings in the section of the conclusion. In the conclusion, I recommend writing the main findings of the study without numbering.

13. Please write limitations of the study and recommendations for future studies at the end of section 6.

Reviewer #2: The paper is indeed interesting, it empirically analyzed the impact of companies in the same industry on corporate environmental EID decisions and tested the formation mechanism and influence path of the industrial homogeneity effect. I think this paper can be accepted for publication provided that it will be scientifically edited to follow the comments.

(1) The Introduction part should start from the phenomena and problems in practice and lead to the research problem.

(2) The literature review should reflect the value of this research, the innovation of this paper and the contribution made by previous studies have not been clearly expressed.

(3) Compared with the available literature, what are the theoretical contributions and application values of this study? It is suggested to enhance the corresponding discussions in the conclusion part.

(4) This article has obtained some interesting findings through the models, but these findings need to be further verified from theory or actual conditions. Also, further highlight the contribution of this article.

(5) Discussion section is missing.

(6) English presentation requires more refinement.

(7) The following literature should be helpful for your research：1）Decoupling economic growth from water consumption in the Yangtze River Economic Belt, China. 2）Coordination of the Industrial-Ecological Economy in the Yangtze River Economic Belt, China. 3) The influence of carbon emission disclosure on enterprise value under ownership heterogeneity: evidence from the heavily polluting corporations.

**********

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Reviewer #1: Yes: Ehsan Elahi

Reviewer #2: No

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13 Aug 2022

Response letter for “PONE-D-22-15667”: Intra-industry peer effect in corporate environmental information disclosure: Evidence from China

I would like to thank the academic editors and reviewers for their valuable comments and suggestions on the article, which provided me with meaningful ideas for revising the article. I will respond point by point to the questions you raised.

Note that in the file labeled “Revised Manuscript with Track Changes”, the green highlights represent adjustments I made based on suggestions from academic editors and reviewers, and the yellow highlights represent changes to grammar, expression, and punctuation.

Academic Editor

Q1: The authors should provide more background information about 1) the general environmental disclosure requirement in China and 2) these two groups. We understand these two groups differ in many different ways. However, the authors should discuss how they differ specifically in corporate environmental information disclosure requirements, and why it is important to understand these differences.

A1: The revisions you proposed are reasonable and can provide a complete theoretical basis for my hypotheses 1b and 1c. I have made sufficient additions to the original text based on the directions you offered (see page 3).

Q2: I suggest you clearly define the peer effect and make sure not to confuse the readers with the peer effect and the learning/imitation effect.

A2: I agree with you that the peer effect is not the same as imitation and learning, but imitation and learning are only one of the reasons for the peer effect. I found a more appropriate definition for the peer effect in my article by reading the literature（see page2 and page3）.

Q3: You find a significant coefficient of age×market, and suggest that the older corporations with information advantages in the market are less affected by the peer effect. Older companies with longer listing years are likely to be companies that have done a better job of environmental compliance and thus require less disclosure. Please discuss further the association between age and peer effect.

A3: In fact, there is now no research evidence that older companies are doing better in environmental compliance. Further, the relationship between environmental compliance and environmental information disclosure, although much discussed at the theoretical level, has not produced a definitive conclusion（Blacconiere and Patten,1994; Rockness,1985; Patten,2002; Dawkins and Fraas,2011; Clarkson, Overell and Chapple,2011）. The relationship between age and peer effects was proposed based on previous studies (Peng,2020). The reasons why younger listed companies are more susceptible to peer effects than older listed companies are as follows. Corporations that have entered the capital market earlier have made more environmental disclosures. These older companies have accumulated more experience in EID and are often considered to have mature disclosure content and paradigms that meet the expectations of investors and regulators. Conversely, young companies in the capital markets make fewer compliance disclosures, have immature models, are still in the discovery stage, and are expected to be more susceptible to peer effects. Part of the above reasons I have already added in the article to show why listing years can be a proxy variable for information advantage (see page6).

Q4: H3 focuses on the environmental protection pressure mechanism. The regression coefficient of press × market is 3.909 and significant and indicates that corporations facing greater environmental protection pressure are more inclined to imitate the peer enterprises' EID. Could you explain why the pressure variable by itself is negative (-33.413***) and highly significant?

A4: Because of the addition of the interaction term MARKETi,t-1×PRESSi,t in Model 3, the coefficients of both MARKETi,t-1 and PRESSi,t are significantly affected, becoming incomparable and changing the economic meaning. This is why the coefficient of Press (-33.413***) in the results shows a serious discrepancy with the facts. In order to accurately estimate the coefficients of MARKETi,t-1 and PRESSi,t, the variables MARKETi,t-1 and PRESSi,t are centered with reference to the study of Balli and Sørensen. This also makes the coefficients of PRESSi,t (5.878***) comparable and in line with expectations. This change is explained in my article (see page8) and the regression results table is updated (see page10). I did not perform the above centrality process before because I used to focus only on the interaction term in the regressions for the moderating variable test. I apologize for the misunderstanding due to my oversight.

Q5: Please thoroughly edit your manuscript for consistency in writing, such as spacing, capitalization, and fonts. Please add pagination as well.

A5: I have carefully checked the above issues and have corrected them in the yellow highlighted areas of the article. Also, I have added page numbers to the article.

Reviewer #1

Q1: The abstract must be started with the main objectives of the study.

A1: Based on your comments, I have added the main objectives of the article at the beginning of the abstract (see page1).

Q2: The main policy must have to provide at the end of the abstract.

A2: Thank you for your suggestion, I have added the policy implementation at the end of the abstract (see page1).

Q3: In the first paragraph of the introduction the given sentence “A large number of studies have shown that the largest source of environmental pollution comes from corporate production and operation activities” must have to revise and update with the given studies as “The studies showed that industrial and agricultural sectors are the main sources of environmental pollution and climate change [1-4]

A3: The revision you provided is reasonable. I have revised it and added the literature you provided to my references (see page1 and reference list).

Q4: Moreover, the given sentence “Thus corporations should expand the scope of entrusted responsibilities and assume the responsibility for environmental management and protection” has to be updated with the given studies as “Understanding of the adoption measures are necessary to mitigate climate change and excessive use of fossil fuel [5,6]”.

A4: The research you provided is valuable and I have introduced its conclusion into the article, but I also kept the original sentences at the same time for logical coherence (see page1 and reference list).

Q5: I recommend adding research questions at the end of section 1.

A5：Based on your suggestion, I have added research questions at the end of section 1 (see page2).

Q6: For equation 1, have you checked the normality of the error term (ε)? You must have to determine the normality of the error term. Or alternatively, you may write an assumption in the revised article as “The error term is assumed to be normality distributed with zero mean value and constant variance [7]”

A6: Thank you for your careful check, I have added the relevant assumptions by referring to the literature you provided (see page7 and reference list).

Q7: The heading of section 4 should write as “Results and discussion”

A7: I made the changes to this section title (see page8).

Q8: In table 3, you must have to write expansions of Std. Dev., Min and Max

A8: I have modified the table3 expression.

Q9: The results must have been compared with previous studies.

A9: This is a very important suggestion, and I add a comparison with previous studies in the article (see page9&page10).

Q10: Equations 4, and 5 should be part of the methodology section.

A10: Referring to the format of other studies, it may be difficult to put model 4 and model 5 into section3 for explanation in order to keep the logic of the article and the independence of further studies. But the methods used in further studies I have made additional elaborations and put them before model 4 and model 5 (see page12&page14), and I hope you will agree with my revision.

Q11: The heading of section 6 should write as “Conclusion and policy implications”

A11: I made the changes to this section title (see page15).

Q12: Please don’t number the study findings in the section of the conclusion. In the conclusion, I recommend writing the main findings of the study without numbering.

A12: As you suggested, I have streamlined the conclusion and removed the numbering (see page15).

Q13: Please write limitations of the study and recommendations for future studies at the end of section 6.

Q13: In the revised version, I have added limitations of this paper and suggestions for future research.

Reviewer #2

Q1: The Introduction part should start from the phenomena and problems in practice and lead to the research problem.

A1: Based on your advice, I reorganized the writing logic of the introduction section (see page1 and page2). The logic after the change is as follows. The importance of improving corporate environmental information disclosure - What factors have been found in existing studies to influence the level of corporate environmental information disclosure - The mutual influence of corporate environmental information disclosure has not been studied in depth - How to use the interaction between companies to improve the level of environmental information disclosure - Present the issues of concern in this paper.

Q2: The literature review should reflect the value of this research, the innovation of this paper and the contribution made by previous studies have not been clearly expressed.

A2: In the revised version, I refine the contributions and shortcomings of existing research, describe the value of this study to the theoretical system, and illustrate the importance of the research questions in this paper (see page2).

Q3&Q4：Compared with the available literature, what are the theoretical contributions and application values of this study? It is suggested to enhance the corresponding discussions in the conclusion part. This article has obtained some interesting findings through the models, but these findings need to be further verified from theory or actual conditions. Also, it further, highlights the contribution of this article.

A3&A4：Based on your two valuable suggestions, I have made content changes in the conclusion section of the article, including highlighting the theoretical contributions of the paper and discussing the implications of this research for policy enactment (see page15).

Q5: The discussion section is missing.

A5：Under the guidance of two reviewers, the title of section4 was changed to “Results and Discussion” (see page8). At the same time, I strengthened the interpretation and discussion of the results and the comparative analysis with existing studies in this section. I hope these changes will meet your expectations.

Q6: English presentation requires more refinement.

A6: In the yellow highlighted section of the revised text, I fixed grammar and formatting errors and refined the English expressions.

Q7: The following literature should be helpful for your research：1）Decoupling economic growth from water consumption in the Yangtze River Economic Belt, China. 2）Coordination of the Industrial-Ecological Economy in the Yangtze River Economic Belt, China. 3) The influence of carbon emission disclosure on enterprise value under ownership heterogeneity: evidence from the heavily polluting corporations.

A7: The literature you provided is very valuable and I have cited them all in my article (see page1). Thank you for your suggestions and guidance.

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6 Sep 2022

Intra-industry peer effect in corporate environmental information disclosure: Evidence from China

PONE-D-22-15667R1

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14 Sep 2022

PONE-D-22-15667R1

Intra-industry peer effect in corporate environmental information disclosure: Evidence from China

Dear Dr. Hao:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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PLOS ONE