Research on Performance Evaluation of Coal Enterprises Based on Grounded Theory, Entropy Method and Cloud Model from the Perspective of ESG

Abstract

At present, coal enterprises generally have inadequate environmental protection, serious social issues, and poor corporate governance. Against the background of sustainable development strategies and the “carbon peaking” and “carbon neutrality” targets, there is an urgent need to conduct a performance evaluation of the sustainable development of coal enterprises. Environmental, social, and governance (ESG) performance is the foundation and booster of sustainable and high−quality development of coal enterprises. It is a typical application of sustainable development and performance evaluation theory to carry out ESG−led performance evaluation and case research of coal enterprises. Therefore, in this paper, we construct the model framework of ESG–grounded theory–entropy method–cloud model to research the performance evaluation of coal enterprises under the guidance of sustainable development from the dimensions of theoretical optimization and case analysis. The model framework includes the factor structure model, performance evaluation index system, index weighting model, and performance evaluation model. First, on the basis of the theory of ESG and triple bottom line, the finance–environment–society–governance (FESG) structural dimension model of coal enterprise performance evaluation was extracted through the three-level coding of grounded theory (GT). On this basis, the performance evaluation index system from the perspective of sustainable development was constructed. Second, on the basis of the entropy method (EM), the weight model of the coal enterprise performance evaluation index was constructed to determine the weight of indexes at all levels. Third, the performance evaluation model was constructed on the basis of the cloud model (CM), and the principles and methods of “dividing index grade, normalizing index grade, calculating index grade membership degree, and evaluating enterprise performance grade” were clarified. Fourth, in order to verify the feasibility of the model framework, a typical listed company (enterprise Z) in the coal industry was selected in order to conduct a case research based on the statistical data from 2016 to 2020 and analyze the performance grade evaluation results. The research shows that (1) the FESG structural dimension model extracted by grounded theory analysis method and the performance evaluation index system of coal enterprises oriented by sustainable development enrich the connotation and extension of ESG theory; (2) the index weighting model based on the entropy method can objectively determine the weight of indicators at all levels of each dimension of performance; (3) the construction path of coal enterprise performance evaluation model based on cloud model can be used to construct performance evaluation models for other industries; (4) the model framework based on the ESG–grounded theory–entropy method–cloud model can be used to reasonably measure the performance level of coal enterprises and provide theoretical support for the research of performance evaluation inside and outside the industry; (5) the sustainable development performance of coal enterprises is the basis and guarantee for achieving sustainable and high-quality development. The research results can provide theoretical reference for the regulatory authorities to formulate performance evaluation policies from the perspective of sustainable development.

1. Introduction

With rapid economic development, the situation with respect to global resources, energy consumption, and environmental destruction is increasingly difficult, and environmental pollution and social contradictions are becoming more and more apparent. Therefore, the question of how to realize the sustainable development of the global economy and human society has gained international attention. Sustainable development is one of the strategies of China’s economic development. The Chinese government has gradually put sustainable development into practice, promoted high-quality economic growth, and thoroughly implemented the 2030 Agenda for Sustainable Development. Concretely speaking, in 2015, the Communist Party of China put forward the “Five Development Concepts” of “innovation, coordination, green, openness, and sharing” at the Fifth Plenary Session of the 18th CPC Central Committee [1]. In the same year, the Chinese government announced the goal of capping carbon dioxide emissions by 2030 under the Framework of the Paris Agreement and incorporated the concept of low-carbon economy construction into the national economic and social development plan [2]. To fully realize the goal of reaching a carbon peak by 2030 and becoming carbon neutral by 2060, the Chinese government has written the goals of “carbon peak” and “carbon neutral” into the Government Work Report 2021 [3]. These practices fully demonstrate the determination of the Chinese government to achieve sustainable development. Environment–social–governance (ESG) incorporates environmental protection, social responsibility, and corporate governance into enterprise performance evaluation, which is a value regarding how to coordinate the development of environment, society, and governance. Enterprise ESG performance integrates the evaluation values of ecological, social, and governance dimensions, covering a wide range of non-financial factors such as promoting sustainable economic development and fulfilling social responsibilities. At the same time, ESG has financial relevance, which is very important to promote the sustainable and high-quality development of enterprises. It can comprehensively evaluate the realization of enterprises’ goals of high-quality economic development, carbon neutrality, and reaching a carbon peak. In practice, enterprises, investors, and researchers continue to pay more attention to ESG, and the global ESG investment continues to climb and currently exceeds USD 30 trillion [4]. China’s attention to ESG is also growing. According to the China ESG Development Report (2021), the number of A-share listed companies issuing ESG-related reports has increased year by year. There were 872 in 2018 and 1130 in 2021. Correspondingly, the overall disclosure rate is also rising slowly and steadily. Moreover, the proportion of companies issuing ESG-related independent reports in A-share listed companies increased from 24.9 % in 2018 to 26.9 % in 2021 [5]. In addition, the disclosure rate of CSI 300 enterprises is close to 90%, far more than small- and medium-sized enterprises [5]. The practice has proven that the research and promotion of the ESG concept are of great significance for implementing sustainable development, promoting supply-side structural reform, improving the efficiency of financial services to the real economy, and supporting economic transformation and growth. Coal is one of China’s core energy sources. For a long time, coal has occupied a dominant position in China’s energy production and consumption structure and is the most secure, economic, and reliable energy asset. China’s coal production is high, and coal enterprises are necessary to support national economic development and to be an essential carrier of internal economic circulation. However, with the acceleration of the replacement of coal with new energy, coal demand is slowing down. The clean and efficient utilization of coal is imminent, and there is an urgent need to realize the sustainable and high-quality development of the coal industry. Moreover, the phenomenon that the development status of coal enterprises is difficult to meet the requirements of sustainable development generally exists. Therefore, the sustainable development level of coal enterprises is of concern. In order to measure the sustainable development level of coal enterprises, there is also an urgent need to establish a set of evaluation mechanisms that can effectively evaluate the performance with respect to the sustainable development of coal enterprises.

The performance evaluation of coal enterprises in China is mainly based on the traditional performance evaluation method. Most research results focus on one aspect of economic performance, environmental performance, or social responsibility performance [6,7,8]. In addition, economic, and financial performance are the primary evaluation objects. Some scholars have studied the environmental, social, and other non-financial performance of coal enterprises, but the research still needs to be deepened [9,10,11,12,13]. Therefore, the exploration and research on the following issues has important value that can fill the gaps in related research. What dimensions do sustainable development performance of coal enterprises include from the perspective of ESG? What dimensions do sustainable development performance evaluation index system include? How do we evaluate the environmental performance, social performance, and governance performance of coal enterprises? What dimensions are the key factors affecting the sustainable development of coal enterprises? Which dimensions should be used to build the performance evaluation model of sustainable development of coal enterprises? How do we combine the ESG concept with sustainable development performance evaluation of coal enterprises? How do we solve the problem that the relevant data are not easy to obtain and have ambiguity in the process of performance evaluation of coal enterprises? How do we build a reasonable model framework for sustainable development performance evaluation?

In order to enrich the existing research content of the performance evaluation of coal enterprises, expand the existing research ideas of the performance evaluation of coal enterprises, promote the improvement of the sustainable development ability of coal enterprises, and promote the promotion and implementation of ESG in the coal industry, in this paper, we propose the construction of the performance evaluation model framework of coal enterprises on the basis of the ESG concept, so as to scientifically evaluate the sustainable development performance of coal enterprises. We combine financial performance with ESG performance and comprehensively evaluate the sustainable development performance of coal enterprises from the four dimensions of finance, environment, society, and governance by applying grounded theory. Then, the key factors affecting the sustainable development of coal enterprises are analyzed. At the same time, aiming at the problems that the relevant data of the performance evaluation of coal enterprises are not easy to obtain accurately and have fuzziness and randomness, the entropy-cloud model is introduced to construct a performance evaluation model of coal enterprises. Finally, the model framework of coal enterprise performance evaluation from the perspective of sustainable development is formed on the basis of ESG, grounded theory, entropy method, and cloud model.

Firstly, on the basis of the triple bottom line theory and ESG concept, the connotation of sustainable development performance of coal enterprises was clarified, and the grounded theory analysis method was used to construct the finance–environment–society–governance FESG structural dimension model through three-level coding and combined with the characteristics of coal industry enterprises. On this basis, 35 specific indicators were extracted, and the performance evaluation index system of coal enterprises was established. Secondly, the entropy method was used to construct the weight model of coal enterprise performance evaluation index. Thirdly, the performance evaluation model of coal enterprises was constructed on the basis of the cloud model. At the same time, the index grade was divided, and the index grade was processed by normal cloud, and the membership degree of the index grade was determined. On this basis, the overall performance, financial performance, environmental performance, social performance, and governance performance of the enterprise were evaluated by integrating the weight and grade membership degree. Fourthly, taking enterprise Z as an example, a case analysis was conducted on the basis of statistical data to calculate its overall performance and performance levels for each dimension from 2016 to 2020. The scientificity and rationality of the model framework of ESG–grounded theory–entropy method–cloud model was verified from the perspective of sustainable development. Finally, the case analysis results were found to be consistent with the reality, which indicates the feasibility of coal enterprise performance evaluation according to the model framework of ESG–grounded theory–entropy method–cloud model.

Compared with the existing literature, the main contributions and innovations of this paper are as follows. (1) Firstly, from the perspective of theoretical mechanism: (i) On the basis of the ESG concept, sustainable development concept, and triple bottom line theory, we creatively combined financial performance with ESG performance and established a comprehensive research mechanism for sustainable development of coal enterprises. (ii) On the basis of the grounded theory, the FESG structure dimension model and performance evaluation index system were creatively constructed from the four dimensions of finance, environment, society, and governance. (iii) We innovatively evaluated the financial performance and non-financial performance of coal enterprises, and comprehensively evaluated the sustainable development performance of coal enterprises. The above theoretical mechanism research content optimizes the limitation that most existing research results focus on one aspect of economic performance, environmental performance, or social responsibility performance. For example, the operating performance, low-carbon performance, and social responsibility performance of coal enterprises are studied separately. (2) Secondly, from the perspective of model and method: (i) We innovatively built the performance evaluation model of coal enterprises on the basis of the entropy method and cloud model. It is the first time that the cloud model has been applied to the performance evaluation of coal enterprises, which verifies a new research method for the performance evaluation of coal enterprises and also provides a new research idea for the performance evaluation of enterprises in other industries. (ii) The combination of entropy method and cloud model can integrate their advantages, overcome the shortcomings and limitations of using one method alone, and make the weight and evaluation results more objective and clear. (3) We innovatively constructed the model framework of ESG–grounded theory–entropy method–cloud model and established the theoretical mechanism analysis mode of coal enterprise performance evaluation on the basis of ESG-GT and the model construction mode of coal enterprise performance evaluation on the basis of EM-CM. The above model framework, theoretical mechanism analysis mode, and performance evaluation model construction mode can provide reference for other industries to carry out the theoretical research and practical work of sustainable development performance evaluation.

The remainder of this paper is arranged as follows. Section 2 is devoted to a literature review. Section 3 analyzes the theoretical mechanism on the basis of ESG and grounded theory and constructs the structural dimension model and the evaluation index system. Section 4 constructs the performance evaluation model on the basis of the entropy method and cloud model. Section 5 verifies and empirically analyzes the model framework of ESG–grounded theory–entropy method–cloud model on the basis of case enterprises. Section 6 presents research conclusions, policy recommendations, and limitations of the research. The research path of this paper is shown in Figure 1.

2. Literature Review

2.1. ESG

Overall, ESG can be traced back to the 1950s. After a long period of gestation and development, the concept of ESG was formally proposed by the UN Global Compact for the first time in 2004. In addition to financial indicators such as revenue and profits, enterprises must consider non-financial indicators at the environmental, social, and governance levels; formulate more accurate business strategies; improve sustainable development performance; and disclose relevant information [14]. In 2006, the United Nations issued the Principles for Responsible Investment (PRI), which significantly promoted the promotion and implementation of ESG [14]. On this basis, many researchers and research institutions have carried out a large number of studies on ESG definition [15,16,17], ESG information disclosure [18,19,20], and ESG performance evaluation [21,22]. Among them, China introduced the concept of ESG late, and the relevant research results began to appear in 2018 and are still in the preliminary exploration stage.

Specifically, first, in terms of the connotation definition of ESG, all definitions of ESG used in countries around the world have the common ground that they all focus on the performance of enterprises from the perspectives of environment, society, and governance. Moreover, the basic connotation is the same. The difference only lies in the classification and specific indicators within each field. At present, the international community has not formed a unified and authoritative definition of ESG, but many scholars, institutions, and organizations have put forward their own representative definitions. The typical examples are as follows. (1) ESG refers to taking environmental (E), social (S), and corporate governance (G) considerations as indicators to influence investment decisions. Following the triple bottom line theory of economy, environment, and society, ESG is integrated into investment analysis and the investment decision-making framework. (2) ESG refers to the performance of enterprises in various issues related to environment, society, and corporate governance, being a tool for enterprise performance evaluation. (3) ESG is a responsible investment strategy that requires the integration of environmental, social, and corporate governance risks into investment analysis. (4) ESG means that enterprises follow the new development concept of “innovation, coordination, green, development and sharing” to maximize value creation in terms of environment(E), society (S), and governance (G), so as to enhance the willingness, behavior, and performance of social welfare [23,24,25,26,27].

Second, the case of ESG information disclosure. ESG information disclosure refers to the disclosure of environmental-, social-, and corporate-governance-related information by enterprises. ESG information disclosure can improve the information transparency and risk management ability of enterprises, strengthen the social responsibility of enterprises, and promote the process of sustainable development of enterprises [28,29,30]. ESG information disclosure in western countries is dominated by relevant institutions and industry associations, and the disclosure framework and principles are relatively perfect. ESG information disclosure rules are mainly principles and framework guidelines that are not legally binding issued by some international organizations. They mainly include the United Nations Organization for Principles of Responsible Investment (PRI); Corporate Governance Standards, Guidelines on Social Responsibility (ISO26000); Guidelines on Information Disclosure for Listed Companies ESG; Guidelines on Sustainable Development Reporting; and Accounting Standards integrated into ESG, among others. Altogether, ESG disclosures are of high quantity and quality in Western countries. In China, ESG is dominated by the government, and the amount of information disclosed relating to ESG is small. The level of disclosure and quality of data are low, so it still needs to be continuously developed and improved [31,32,33]. However, with the rapid development of international ESG information disclosure, Chinese government regulatory authorities and relevant institutions have also begun to formulate relevant laws and regulations, policy documents, and disclosure guidelines to promote enterprises to regularly disclose ESG-related information. The principles and framework of ESG information disclosure inside China include the Announcement on Corporate Environmental Information Disclosure; Guidelines on Social Responsibility of Listed Companies on the Shenzhen Stock Exchange; Guidelines on Environmental Information Disclosure of Listed Companies on the Shanghai Stock Exchange; Corporate Governance Guidelines; Science and Technology Innovation Board Stock Listing Rules; Environmental, Social and Governance (ESG) Reporting Guidelines; the Reform Plan of Environmental Information Disclosure System According to the Law, and the Annual Report Format Guidelines. At the same time, Chinese listed companies are facing increasingly stringent ESG disclosure requirements.

Third, there is the case of terms of ESG performance rating and evaluation [34,35,36]. ESG performance evaluation is based on ESG information disclosure and provides a method of evaluation and comparison, which is a key factor in the development of the ESG system. The content of ESG performance rating and evaluation includes three dimensions: environmental, social, and governance, as well as the specific areas involved in each dimension that enterprises need to consider in their operation. ESG performance rating is mainly carried out by rating agencies. Different rating agencies consider different factors and adopt different specific evaluation indicators and methods. Moreover, each has an independent methodology for calculating and evaluating ESG performance. International ESG rating agencies are mainly divided into two categories: enterprises or profit-making institutions, and environmental groups. The representative ESG rating agencies are S&P Dow Jones, Thomson Reuters, FTSE Russell, KLD, MSCI, etc. Moreover, the ESG indexes launched by these institutions include the Dow Jones index, the FTSE social responsibility index, and the MSCI index. ESG rating agencies in China are mainly divided into two categories: enterprises or associations, and university research institutes. Among them, the representative ESG rating agencies are SynTao Green Finance, Rankins ESG Ratings, Harvest Fund, Green Finance International Research Institute of Central University of Finance and Economics, Asset Management Association of China, etc. Moreover, the ESG indexes launched by these rating agencies include the SynTao Green Finance ESG Good 50 Index (SGCX ESG50), the CSI 180ESG Index, and the CSI 300 Green Leading Index. In a word, the development of ESG performance rating outside China is relatively high, while there are few relevant studies inside China, and a perfect and unified ESG evaluation system has not been established yet [37,38,39,40,41,42,43].

2.2. Enterprise Performance Evaluation

Researchers started the research on enterprise performance evaluation earlier, and the research on enterprise performance evaluation successively experienced the stages of the cost performance evaluation in the 19th century, the financial performance evaluation in the 20th century, and the comprehensive performance evaluation since the dawn of the 21st century [44,45,46].

Specifically, in the stage of cost performance evaluation, enterprise owners hold the ownership and management rights, and the key for enterprises to gain competitive advantages lies in effective cost control. Most of the research results in this stage are concentrated in western countries, and the representative scholars are Taylor and Harry. On the basis of Taylor’s management ideas, Harry put forward the standard cost system in 1911, which significantly improved the cost performance of enterprises.

In the stage of financial performance evaluation, the ownership and operation of enterprises are separated. In order to ensure their own interests, the stakeholders who do not participate in the actual operation of the enterprise begin to pay attention to the operating results and financial conditions of the enterprise. In this context, scholars began to study the financial performance of enterprises, and a large number of research results emerged. At this stage, research achievements including the DuPont analysis system, the Wall scoring method, and EVA index emerged in western countries. In China, research achievements are mainly financial performance evaluation standards and documents formulated by the government. They mainly include the General Principles of Enterprise Finance issued by the Ministry of Finance of the People’s Republic of China in 1993, and the Index System of Enterprise Economic Performance Evaluation (Trial) issued by the Ministry of Finance of the People’s Republic of China in 1995.

In terms of the stage of comprehensive performance evaluation, since the 21st century, the traditional financial performance evaluation mechanism has been unable to meet the needs of all stakeholders. The enterprise performance evaluation index system is becoming increasingly more comprehensive and complex, and the enterprise performance evaluation methods are becoming increasingly more diverse [47]. During this period, theoretical concepts and models such as balanced scorecard, “triple earnings” performance, and performance prism model emerged in western countries. On the basis of the theoretical achievements of western countries, Chinese scholars have conducted more specific and in-depth research on the theories and methods of enterprise performance evaluation for different industries and achieved a large number of research results.

As a whole, most of the current research results still focus on the evaluation of economic performance. Although some index systems also take into account the environmental and social performance of enterprises, they are not comprehensive and lack industry pertinence [48,49,50]. For coal enterprises with high pollution and high energy consumption, it not only creates economic benefits, but also brings about negative environmental and social impacts. Therefore, a set of enterprise performance evaluation systems based on sustainable development should be established as soon as possible to evaluate the comprehensive performance of such enterprises in economic, environmental, and social aspects, as well as promote their sustainable development[11,13,51,52,53,54,55,56,57].

2.3. ESG and Enterprise Performance Evaluation

With the continuous development of the ESG concept, the influence of ESG level on enterprise performance has been of widespread concern by scholars. At present, most researchers believe that the higher the ESG rating, the better the enterprise performance, that is, ESG performance has a positive impact on enterprise performance [58,59,60]. A few researchers believe that ESG performance has a negative impact on enterprise performance [61]. As ESG is an investment concept and evaluation standard that focuses on non-financial performance such as enterprise environment, society, and governance, the combination of ESG and financial indexes can measure the comprehensive performance of enterprises and evaluate their sustainable development level [62,63]. Therefore, some researchers studied the enterprise performance evaluation system on the basis of ESG, integrated ESG indicators into the enterprise performance evaluation system, combined non-financial indicators with financial indicators, and comprehensively evaluated the sustainable development performance of enterprises [64]. However, few studies have investigated the performance evaluation of coal enterprises on the basis of the ESG concept.

3. Theoretical Mechanism of Coal Enterprise Performance Evaluation Based on Grounded Theory from the Perspective of ESG

3.1. Structural Model of Coal Enterprise Performance Evaluation Elements Based on Grounded Theory

3.1.1. Grounded Theory

In 1967, Barney Glaser and Anselm Strauss proposed grounded theory (GT) in their monograph Grounded Theory Discovery: Strategies for Qualitative Research. It is centered on progressive case selection, data collection, and comparison between theory and data [65,66]. Systematic procedures are used to conclude and mine the data. The qualitative research method aims to integrate the researcher into the research environment, collect data using various methods, study social phenomena, induce and analyze data to form theories, and obtain explanatory understanding [67]. The grounded theory combines systematic analysis methods of qualitative and quantitative research. Qualitative methods are used in research design and data collection, while quantitative methods are used in data analysis. At the same time, grounded theory is a bottom-up theoretical research method used to construct relevant theories on the basis of the induction and summary of original data. It is crucial to conduct sociological research from observation rather than hypothesis. The grounded theory requires researchers to sort the collected data from a new perspective. Coding and analyzing a large amount of data to establish new theories or enrich existing ones is an approach that is suitable for studies that lack theoretical explanations or have insufficient theoretical grounds due to their exploratory characteristics [68]. The induction and deduction process of grounded theory includes problem definition, literature review, data collection, data coding, development, and construction of a theoretical model, with data collection and coding being the core steps [68,69].

In existing studies, there is a lack of literature and materials on performance factors and evaluation of coal enterprises from the perspective of ESG, and there is a lack of similar experience or mature theories to support the research on performance factors and evaluation of coal enterprises from the standpoint of ESG. The evaluation dimensions and emphases are characterized by multiplicity, complexity, and difficulty in quantification. Meanwhile, studies on ESG and the performance of coal enterprises are mainly based on secondary data. The empirical analysis is conducted on the relationship between traditional variables, while scenario verification of first-hand in-depth interview data and policy data is lacking. At the same time, there are plentiful practical data on policies and standards of ESG and performance evaluation of coal enterprises. Still, it is difficult to directly extract evaluation indicators of coal enterprises from existing studies by literature analysis.

Therefore, we used grounded theory to explore the factor structure of coal enterprise performance from the perspective of ESG, analyzed the influencing factors of coal enterprise performance from the perspective of ESG, and elaborated on its action mode and logical structure. Firstly, on the basis of policy and interview data of ESG and coal enterprise performance factors, following the research paradigm and research path of grounded theory, through open coding, concepts were extracted and developed from the original data to form the initial category of coal enterprise performance from the perspective of ESG. Next, through spindle coding, repeated comparison, and test concepts, we refined and distinguished these initial categories and extracted the primary categories of coal enterprise performance from the perspective of ESG. Next, core categories covering all other genera were identified by selective coding. Finally, a theoretical saturation test was conducted to construct the theoretical model of structural dimensions of performance factors and the performance evaluation index system of coal enterprises from the perspective of ESG (Figure 2).

3.1.2. Sample Selection and Data Collection

On the basis of policy data of ESG and coal enterprise performance and in-depth interview data of coal enterprise performance, sample selection and data collection of grounded theory were conducted.

Policy Data on ESG and Coal Enterprises Performance

First, the keywords and retrieval methods of policy data were determined. The keywords related to ESG included “ESG”, “ESG performance”, and “ESG evaluation” in Chinese and English. The keywords related to the performance evaluation of coal enterprises included “performance evaluation of coal enterprises”, “financial performance of coal enterprises”, “environmental performance of coal enterprises”, “social responsibility performance of coal enterprises”, and “corporate governance performance of coal enterprises” in Chinese and English. The keywords related to ESG and performance evaluation of coal enterprises were also comprehensively searched for and retrieved according to their combination, such as “performance evaluation of coal enterprises based on ESG”. Next, through exploring the above-mentioned keywords on various literature and data platforms, reading, and the sorting out of relevant literature, a total of 31 applicable guidelines, documents, evaluation index systems, standards, and books, including the Interim Measures for the Management of Comprehensive Performance Evaluation of Central Enterprises and other policies, were collected. The terminated policies and notification documents with similar contents were removed, and 26 policy texts (numbered 1 to 26) were selected as the analysis objects. (Among them, 21 were used as initial coding samples, and 5 were used for conducting the theoretical saturation test.) The policy data on ESG and coal enterprise performance is provided in the Attachment.

In-Depth Interview Data on ESG and Coal Enterprise Performance

The grounded theory emphasizes the breadth and depth of data sources. Therefore, in addition to policy data, we collected relevant data through in-depth interviews to supplement and cross-verify research conclusions using diversified information. To be a valid approach, interviewees should cover all stakeholders. Coal enterprise stakeholders are individuals or groups whose interests may be affected by enterprise decisions or activities. We selected interview samples from the perspectives of stakeholders, including shareholders, creditors, suppliers, retailers, consumers, government, and enterprise employees. The personal information of the interviewees was collected through questionnaires; the time, location, and content of the interview were sorted; and finally, the text was formed. The grounded theory emphasizes the representativeness of samples and the richness of data sources. We determined the number of samples according to the theoretical saturation principle in which samples continue to be taken until the new sample no longer provides new information. Per the principle of theoretical sampling and data availability, 30 objects (25 as initial coding samples and 5 for the theoretical saturation test) were finally determined as research samples.

We conducted in-depth interviews with 30 interviewees, applying the principles of openness and directivity in the interview process. First, open questions with ESG and coal enterprise performance evaluation as the core were designed in advance, and an interview outline was formed. This approach allowed the interviewees to express their views on the basis of divergent thinking, which is conducive to the three-level coding of grounded theory. Next, the concept, meaning, and characteristics of ESG and performance evaluation were explained to the interviewees to ensure that the interviewees fully understood the influencing factors of the coal enterprise performance evaluation from the perspective of ESG. Then, we conducted in-depth, face-to-face interviews with the interviewees, strictly following the grounded theory research paradigm. Video and audio recordings were made of the interview process and converted into written documents, to which we added notes on the voice content such as tone and expression and on-the-spot observations. Finally, 36 primary transcripts of in-depth interviews were obtained, of which 30 remained after removing invalid recordings. The interview audio totaled 600 min, and the data totaled more than 40,000 words, with an effective rate of 83.3%, as a basis for grounded theory analysis. The interview materials were repeatedly discussed, analyzed, screened, and processed in strict accordance with the definitions of ESG and performance evaluation of coal enterprises and numbered to facilitate data processing and analysis [69].

In summary, the original data of the grounded theory research in this study were composed of the policy text data related to “ESG and performance evaluation of coal enterprises” and in-depth interview data. To improve the reliability and validity of the study, 21 policy data and 25 interview data were selected for coding analysis, and the theoretical model was summarized and constructed. The remaining five policy texts and five interview materials were used to test the theoretical saturation, and the controversial concepts and categories were revised and deleted on the basis of expert opinion (

Table 1. Data sources and codes of grounded theory.

Data Source	Data Acquisition Object	Was of Data Acquisition	Purpose	Data Coding
Primary data	Shareholders	Open interview	(1) Understand ESG evaluation related data. (2) Understand relevant data of corporate financial performance, environmental performance, social performance, and governance performance evaluation. (3) Understand the performance evaluation data of coal enterprises.	AX1–AX3
	Creditor	Open interview		AX4–AX7
	Supplier	Open interview		AX8–AX9
	Retailer	Open interview		AX10–AX11
	Consumer	Open interview		AX12–AX13
	Governmental personnel	Semi-structured interview		AX14–AX17
	Scientific research personnel	Structured interview		AX18–AX20
	Participatory observation	Observation and record	Verify the interview data.	BXn
Secondary data	Literature	Reading and organizing	Supporting primary data.	DXn
	Policy data			CXn

).

3.1.3. Data Coding and Category Extraction

Taking the performance of coal enterprises from the perspective of ESG as an example, we used the NVivo 11 Plus software analysis tool, followed by the grounded theory research paradigm and research path, and obtained the categories, main categories, and core categories of coal enterprise performance from the perspective of ESG through open coding, spindle coding, and selective coding. Then, the factors of performance evaluation of coal enterprises from the perspective of ESG were identified, the structural dimension model of performance evaluation was formed, and the index system of performance evaluation of coal enterprises from the perspective of ESG was constructed. The coding format of in-depth interview data is AXn (n = 1, 2, 3, …) and BXn (n = 1, 2, 3, …), the coding format of policy text data is CXn (n = 1, 2, 3, …), and the coding format of literature data is DXn (n = 1, 2, 3, …).

Open coding is the process of organizing, analyzing, and summarizing the original data and realizing the conceptualization and categorization of sample data. It has two main steps: developing the concept and exploring the category [68]. First, the policy text and in-depth interview data were textualized, sentences were interrupted and given subjective meanings, and the meaning of each sentence was compared and analyzed to conceptualize it. Similar concepts were then integrated, coded, labeled word for word, and distilled into categories that summarized similar concepts.

Developing the Concepts

The first step was to define the phenomenon, split the original data sentence by sentence, then classify the split sentences according to different meanings, and summarize the essence of each sentence’s meaning, a process known as conceptualization. In developing concepts, it is necessary to establish templates to integrate and optimize similar or identical concepts and constantly compare, modify, and improve them. For example, we chose any word that appeared more than four times in the definition phenomenon (labeling) as the initial concept to define the category further and mark it as Xn (n = 1, 2, 3 …). In the later stage of the conceptualization process, the probability of repeating the previous concepts will be increasingly higher until no new concepts are generated. At that point, the conceptualization process is complete [66]. A total of 75 original concepts were developed in this paper.

Exploring the Categories

Exploring categories involves integrating identical concepts and carrying out a deeper abstraction and concentration to obtain the category that can summarize similar concepts. On the basis of the analysis path of “original data phenomenalization→conceptualization→categorization”, the concept itself was categorized according to the specific context connotation and its extension, and a total of 44 categories such as return on equity and operating profit rate were obtained and labeled An (n = 1, 2, 3 …). These 44 categories were the most frequent and common factors in policy texts and in-depth interview materials, which were thus identified as the key influencing factors of coal enterprise performance from the perspective of ESG. The process of open coding is shown in

Table 2. Open coding.

Original Data		Encoding Process
Data Name	Data Source	Original Concept	Category
CX1: Interim Measures for the Administration of Comprehensive Performance Evaluation of Central Enterprises	State-owned Assets Supervision and Administration Commission of the State Council—SASAC	X1 Return on equity, X2 Return on total assets, X3 Operating profit margin, X4 Earnings cash guarantee multiple, X5 Ratio of profits to cost and expense, X6 Return on capital, X7 Total asset turnover rate, X8 Accounts receivable turnover ratio, X9 Inventory turnover, X10 Proportion of non-performing assets, X11 Current assets turnover rate, X12 Cash return on assets, X13 Asset–liability ratio, X14 Ratio of total profit before interest tax to interest expenditure, X15 Quick ratio, X16 Cash flow liability ratio, X17 Interest-bearing debt ratio, X18 Contingent liabilities ratio, X19 Growth rate of total operating income, X20 Rate of capital ensure and increase in value, X21 Growth rate of operating profit, X22 Growth rate of total assets,	A1 Return on equity
CX2: Implementation Rules for Comprehensive Performance Evaluation of Central Enterprises	State-owned Assets Supervision and Administration Commission of the State Council—SASAC		A2 Operating profit margin
CX3: Standard Value of Enterprise Performance Evaluation (2021)	State-owned Assets Supervision and Administration Commission of the State Council—SASAC		A3 Return on capital
CX4: Environmental Management System Specification and Use Guide (ISO14001)	International Standardization Organization—ISO		A4 Quick ratio
CX5: Guide to Performance Evaluation of Energy Management in Coal Industry	State-owned Assets Supervision and Administration Commission of the State Council—SASAC		A5 Cash flow liability ratio
CX6: Clean Production Standard Coal Mining and Selection Industry (HJ 446-2008)	Ministry of Ecology Environment of the People‘s Republic of China		A6 Asset–liability ratio
CX7: Evaluation Index System of Clean Production in Coal Mining and Selection Industry	National Development and Reform Commission, Ministry of Ecology Environment of the People‘s Republic of China, Ministry of Industry and Information Technology of the People‘s Republic of China		A7 Total asset turnover rate
CX8: Guide Standard for Social Responsibility	International Standardization Organization—ISO		A8 Current assets turnover rate
CX9: Guidelines on Performance Classification of Social Responsibility (GB/T 36002-2015)	National Standardization Committee		A9 Accounts receivable turnover ratio
CX10: Specification for Occupational Health and Safety Administration System (OHSAS 18001)	British Standards Institution—BSI		A10 Growth rate of total operating income
CX11: Guidelines for the Compilation of Corporate Social Responsibility Reports in China Coal Mining and Selection Industry (CASS-CAR3.0)	CASS-CAR3.0		A11 Growth rate of operating profit
CX12: Governance Codes for Listed Companies (2018)	China Securities Regulatory Commission—CSR		A12 Growth rate of total assets
CX13: Standard and Poor’s Corporate Governance Evaluation Index System	Standard and Poor’s	X23 Recovery rate of mining area, X24 Comprehensive energy consumption of ten thousand yuan output value, X25 Comprehensive energy consumption of raw coal production, X26 Power consumption in raw coal production, X27 Water consumption in raw coal production, X28 Utilization rate of coal gangue, X29 Mine water utilization rate, X30 Comprehensive utilization rate of production wastewater in mining area, X31 Sulfur dioxide emission reduction rate, X32 Nitrogen oxide emission reduction rate, X33 Chemical oxygen demand reduction rate, X34 Control rate of subsidence area, X35 Land reclamation rate, X36 Greening rate of industrial square, X37 Compliance rate of total pollutant discharge,	A13 Comprehensive energy consumption of raw coal production
CX14: Deminor corporate governance evaluation index System	Deminor		A14 Comprehensive energy consumption of ten thousand yuan output value
CX15: Chinese Listed Companies Governance Evaluation Index System	China Listed Corporate Governance Index—CCGINK		A15 Power consumption in raw coal production
CX16: Guidelines on Information Disclosure of ESG for Listed Companies	United Nations Sustainable Stock Exchange—UNSSEI		A16 Water consumption in raw coal production
CX17: Environmental, Social and Governance (ESG) Reporting Guidelines (2019)	Hong Kong Stock Exchange—SEHK		A17 Recovery rate of mining area
CX18: Research Report on ESG Evaluation System of Chinese Listed Companies (2019)	Asset Management Association of China—AMAC, Development Research Center of the State Council—DRCSC		A18 Utilization rate of coal gangue
CX19: ESG Blue Book of Listed Companies of Central Enterprises (2021)	State-owned Assets Supervision and Administration Commission of the State Council—SASAC		A19 Mine water utilization rate
CX20: SynTao Green Finance ESG Evaluation Index System	SynTao Green Finance Inc.—STGF		A20 Sulfur dioxide emission reduction rate
CX21: ESG Evaluation index system of International Institute of Green Finance, Central University of Finance and Economics	International Institute of Green Finance, Central University of Finance and Economics		A21 Nitrogen oxide emission reduction rate
AX1: Open Interview Data of Shareholders	Interview data		A22 Chemical oxygen demand reduction rate
AX2: Open Interview Data of Shareholders	Interview data	X38 Proportion of R&D personnel, X39 Proportion of R&D expenditure, X40 Number of patents, X41 Social insurance coverage, X42 Labor contract signing rate, X43 Labor employment record rate, X44 Cash ratio paid to employees, X45 Employee per capita annual income growth rate, X46 Qualified rate of occupational hazard factor monitoring, X47 Qualified rate of employee safety education and training, X48 Annual inspection rate of production mine employees, X49 Proportion of safety production input, X50 Coal production death rate per million tons, X51 Number of occurrences of large and major accidents, X52 Coal mining mechanization rate, X53 Proportion of donations and poverty alleviation, X54 Tax contribution rate, X55 Social contribution rate, X56 Social contribution per share,	A23 Proportion of R&D personnel
AX3: Open Interview Data of Shareholders	Interview data		A24 Proportion of R&D expenditure
AX4: Open Interview Data of Creditors	Interview data		A25 Number of patents
AX5: Open Interview Data of Creditors	Interview data		A26 Cash ratio paid to employees
AX6: Open Interview Data of Creditors	Interview data		A27 Employee per capita annual income growth rate
AX7: Open Interview Data of Creditors	Interview data		A28 Social insurance coverage
AX8: Open Interview Data of Suppliers	Interview data		A29 Proportion of safety production input
AX9: Open Interview Data of Suppliers	Interview data		A30 Coal production death rate per million tons
AX10: Open Interview Data of Retailers	Interview data		A31 Tax contribution rate
AX11: Open Interview Data of Retailers	Interview data		A32 Social contribution per share
AX12: Open Interview Data of Consumers	Interview data		A33 Proportion of donations and poverty alleviation
AX13: Open Interview Data of Consumers	Interview data	X57 Proportion of the largest shareholder, X58 Proportion of second to fifth shareholders, X59 Z index, X60 Herfindahl_5 index, X61 Number of shareholders’ meetings, X62 Dividend distribution ratio, X63 Return to shareholders, X64 Board size, X65 Proportion of non-executive directors, X66 Proportion of independent directors, X67 Number of board meetings, X68 Number of executives, X69 Executive shareholding ratio, X70 Proportion of executive compensation, X71 Management expenses ratio, X72 Number of supervisors, X73 Number of meetings of the board of supervisors, X74 Compensation proportion of supervisors, X75 Opinion adoption rate of the board of supervisors	A34 Herfindahl_5 index
AX14: Semi-structured Interview Data of Government Personnel	Interview data		A35 Dividend distribution ratio
AX15: Semi-structured Interview Data of Government Personnel	Interview data		A36 Proportion of the largest shareholder
AX16: Semi-structured Interview Data of Government Personnel	Interview data		A37 Proportion of independent directors
AX17: Semi-structured Interview Data of Government Personnel	Interview data		A38 Number of board meetings
AX18: Structured Interview Data of Scientific Research Personnel	Interview data		A39 Board size
AX19: Structured Interview Data of Scientific Research Personnel	Interview data		A40 Proportion of executive compensation
AX20: Structured Interview Data of Scientific Research Personnel	Interview data		A41 Management expenses ratio
BX: Participatory Observation of Data	Observation data		A42 Number of meetings of the board of supervisors
DX: Literature	Literature		A43 Compensation proportion of supervisors
			A44 Opinion adoption rate of the board of supervisors

.

We used spindle coding to integrate the categories obtained by open coding through the relationship of causality, structure, and time and further analyzed the data to obtain the main categories. Spindle coding aims to establish associations according to the logic, connotation, emotion, and other relations between different categories and improve the explanatory power of models and theories to research questions and social background [68,70]. We reanalyzed and clustered the 44 categories obtained by open coding and established the connection and genus relationship between each category to forge a communication channel between practice and theory. For example, the three categories of “A4 quick ratio”, “A5 cash flow debt ratio”, and “A6 asset–liability ratio” in open coding can be used to measure the debt-paying ability of enterprises. Therefore, these three categories can be integrated into one main category: “debt-paying ability”. The initial categories with the same purpose and similar content were summarized under the same primary category. Through the repeated implementation of this process, 15 main categories such as profitability, debt-paying ability, operating ability, and development ability were extracted (

Table 3. Spindle and selective coding results.

Core Category	Main Category	Category	Core Category	Main Category	Category
Financial performance	Profitability	Return on equity	Social performance	Enterprise scientific and technological innovation	Proportion of R&D personnel
		Operating profit margin			Proportion of R&D expenditure
		Return on capital			Number of patents
	Solvency	Quick ratio		Employee rights and interests	Cash ratio paid to employees
		Cash flow liability ratio			Employee per capita annual income growth rate
		Asset–liability ratio			Social insurance coverage
	Operating capacity	Total asset turnover rate		Safety responsibility	Proportion of safety production input
		Current assets turnover rate			Coal production death rate per million tons
		Accounts receivable turnover ratio		Social contribution	Tax contribution rate
	Development capacity	Growth rate of total operating income			Social contribution per share
		Growth rate of operating profit			Proportion of donations and poverty alleviation
		Growth rate of total assets	Governance performance	Shareholder governance	Herfindahl_5 index
Environmental performance	Energy consumption	Comprehensive energy consumption of raw coal production			Proportion of the largest shareholder
		Comprehensive energy consumption of ten thousand yuan output value			Dividend distribution ratio
		Water consumption in raw coal production		Board governance	Proportion of independent directors
		Power consumption in raw coal production			Board size
	Resource utilization	Recovery rate of mining area			Number of board meetings
		Utilization rate of coal gangue		Managers governance	Proportion of executive compensation
		Mine water utilization rate			Management expenses ratio
	Pollution control and emission reduction	Sulfur dioxide emission reduction rate		Supervisory board governance	Number of meetings of the board of supervisors
		Nitrogen oxide emission reduction rate			Opinion adoption rate of the board of supervisors
		Chemical oxygen demand reduction rate			Compensation proportion of supervisors

).

On the basis of the open and spindle coding, we used selective coding to excavate the core categories from the main categories, established the correlation system between the core category and other categories using a logic diagram, and formed a complete interpretation framework to refine the theoretical model [68]. After analyzing and sorting the original data, initial concepts, categories, and main categories, we drew the following conclusions from the perspective of sustainable development performance: (1) the main categories of “profitability”, “debt-paying ability”, “operating ability”, and “development ability” constitute the financial performance elements of coal enterprises; (2) the main categories of “energy consumption”, “resource utilization”, and “pollution reduction” constitute the environmental performance elements of coal enterprises; (3) the main categories of “scientific and technological innovation”, “employee rights and interests”, “safety responsibility”, and “social contribution” constitute the social performance elements of coal enterprises; (4) the main categories of “shareholder governance”, “board governance”, “managers governance”, and “board of supervisors governance” constitute the governance performance elements of coal enterprises.

3.1.4. Construction of Structural Dimension Model (FESG)

On the basis of the theory of sustainable development, stakeholders, triple bottom line, and ESG, the logical connection statements between the main categories and the functional description of different subjects, according to the core path of “financial performance–environmental performance–social performance–governance performance”, we constructed a FESG structural dimension model of coal enterprise performance evaluation from the perspective of sustainable development (Figure 3).

Financial Performance (F)

For enterprises, economic performance refers to financial performance, which focuses on the transformation and utilization of resources by individual units. The financial performance of coal enterprises refers to the distribution and utilization of existing resources through the implementation of production and management activities that reflect the enterprise value contained in itself and recognized by society [71]. The results obtained by coal enterprises through production and management activities, which can reflect the economic value of coal enterprises, manifested as the structural elements of enterprise profitability, operation ability, debt−paying ability, and development ability.

Environmental Performance (E)

Enterprise environmental performance is the result of an enterprise’s efforts to reduce the impact of its activities on the external environment. In a broad sense, environmental performance refers to the comprehensive effect achieved by enterprises in pollution prevention, resource utilization, and ecological impact. The narrow sense of environmental performance refers to the indicators stipulated in the existing environmental standards and can be directly detected. In the process of production and operation, coal enterprises will have adverse effects on the environment, which is manifested in the excessive consumption of resources and energy, the waste of resources and energy, and the destruction of the ecological environment by a large number of pollutants. Therefore, the environmental performance of coal enterprises can be defined as the achievements made by coal enterprises in resource consumption, comprehensive utilization of energy, pollution reduction, and ecological environment restoration. Its structural elements include resource and energy consumption, comprehensive utilization of energy, and pollution reduction.

Social Performance (S)

Enterprise social performance is derived from corporate social responsibility, and the social performance of coal enterprises refers to the results achieved by coal enterprises in the implementing the core theme of social responsibility and related issues. When measuring the feasibility and effectiveness of social behaviors, enterprises need to consider the impact of social-responsibility-related behaviors on stakeholders. Further combined with the stakeholder theory [72] and the production characteristics of the coal industry, the social performance structure elements of coal enterprises include (1) responsibilities to consumers, such as product liability, etc.; (2) responsibilities to employees, such as ensuring employees’ rights and interests, ensuring production safety, etc.; (3) responsibilities to the government, such as paying taxes on time, etc.; (4) responsibility to the public, such as carrying out corresponding public welfare activities, etc.; and (5) responsibilities to partners, such as on time delivery, etc.

Governance Performance (G)

In a broad sense, enterprise governance refers to the coordination of interests of stakeholders through a set of systems or mechanisms, including formal or informal, internal, or external. In a narrow sense, enterprise governance refers to the supervision and balance mechanism of owners (shareholders) to managers, namely, the internal governance of the corporate governance structure constituted by shareholders’ meetings, the board of directors, and the management [73]. Governance performance of coal enterprises refers to the compliance and effectiveness of internal governance through the corporate governance structure composed of shareholders’ meetings, the board of directors, management, and the board of supervisors. Compliance refers to corporate governance meeting regulatory compliance requirements, and effectiveness refers to increasing corporate value and improving market competitiveness through effective corporate governance. However, after many years of development and improvement, most coal enterprises in the form of corporate governance are relatively complete and meet the requirements of compliance. Therefore, the structural elements of the governance performance of coal enterprises are mainly reflected in the effectiveness of corporate governance, which mainly includes the performance of shareholder governance, board of directors governance, managers governance, and board of supervisors governance in effectiveness.

Five policy texts and five interview datasets were coded and analyzed to test the theoretical saturation. No new initial concepts and categories emerged, and no further changes occurred in the relationship between concepts and categories. Therefore, the FESG structural dimension model of coal enterprise performance evaluation from the perspective of sustainable development was judged to have passed the theoretical saturation test.

3.2. Performance Evaluation Index System of Coal Enterprises Based on ESG-GT

On the basis of recent research results of enterprise performance evaluation and the forming factors of coal enterprise performance, we analyzed the research results of the grounded theory analysis and FESG structural dimension model of coal enterprise performance factors. Following the principles of systematicity, comprehensiveness, applicability, and comparability, and integrating triple performance [74] with ESG performance, a performance evaluation index system including 4 first-level indicators, 15 second-level indicators, and 35 third-level indicators was constructed (

Table 4. Performance evaluation index system of coal enterprises.

Criterion Layer		Sub-Criteria Layer		Practice Layer
First Level Indexes	Weight	Second Level Indexes	Weight	Third Level Indexes (Unit)(Local Weight)	Weight
B1 Financial performance	28.21%	C1 profitability (23.11%)1	6.52%	C1-1 Return on equity (%)(35.28%)	2.30%
				C1-2 Operating profit margin (%)(27.45%)	1.79%
				C1-3 Return on capital (%)(37.27%)	2.43%
		C2 solvency (26.66%)	7.52%	C2-1 Quick ratio (%)(36.44%)	2.74%
				C2-2 Cash flow liability ratio (%)(24.87%)	1.87%
				C2-3 Asset-liability ratio (%)(38.70%)	2.91%
		C3 operating capacity (22.19%)	6.26%	C3-1 Total asset turnover rate (times)(34.50%)	2.16%
				C3-2 Current assets turnover rate (times)(30.83%)	1.93%
				C3-3 Accounts receivable turnover ratio (times)(34.66%)	2.17%
		C4 development capacity (28.04%)	7.91%	C4-1 Growth rate of total operating income (%)(30.97%)	2.45%
				C4-2 Growth rate of operating profit (%)(47.91%)	3.79%
				C4-3 Growth rate of total assets (%)(21.11%)	1.67%
B2 Environmental performance	20.91%	C5 energy consumption (23.18%)	4.68%	C5-1 Comprehensive energy consumption of raw coal production (kg standard coal/ton coal)(100.00%)	4.68%
		C6 resource utilization (34.92%)	7.05%	C6-1 Recovery rate of mining area (%)(26.10%)	1.84%
				C6-2 Utilization rate of coal gangue (%)(47.38%)	3.34%
				C6-3 Mine water utilization rate (%)(26.52%)	1.87%
		C7 pollution control and emission reduction (41.90%)	8.46%	C7-1 Sulfur dioxide emission reduction rate (%)(33.81%)	2.86%
				C7-2 Nitrogen oxide emission reduction rate (%)(41.02%)	3.47%
				C7-3 Chemical oxygen demand reduction rate (%)(25.18%)	2.13%
B3 Social performance	22.97%	C8 enterprise scientific and technological innovation (26.82%)	6.16%	C8-1 Proportion of R&D personnel (%)(69.16%)	4.26%
				C8-2 Proportion of R&D expenditure (%)(30.84%)	1.90%
		C9 employee rights and interests (29.87%)	6.86%	C9-1 Cash ratio paid to employees (%)(53.06%)	3.64%
				C9-2 Employee per capita annual income growth rate (%)(46.94%)	3.22%
		C10 safety responsibility (22.73%)	5.22%	C10-1 Proportion of safety production input (%)(66.48%)	3.47%
				C10-2 Coal production death rate per million tons (%)(33.52%)	1.75%
		C11 social contribution (20.59%)	4.73%	C11-1 Tax contribution rate (%)(52.64%)	2.49%
				C11-2 Social contribution per share (yuan)(47.36%)	2.24%
B4 Governance performance	28.60%	C12 shareholder governance (30.56%)	8.74%	C12-1 Herfindahl_5 index (57.89%)	5.06%
				C12-2 Dividend distribution ratio (%)(42.11%)	3.68%
		C13 board governance (23.18%)	6.63%	C13-1 Proportion of independent directors (%)(56.56%)	3.75%
				C13-2 Number of board meetings (times)(43.44%)	2.88%
		C14 managers governance (16.92%)	4.84%	C14-1 Proportion of executive compensation (%)(57.23%)	2.77%
				C14-2 Management expenses ratio (%)(42.77%)	2.07%
		C15 supervisory board governance (29.34%)	8.39%	C15-1 Number of meetings of the board of supervisors (times)(78.55%)	6.59%
				C15-2 Compensation proportion of supervisors (%)(21.45%)	1.80%

Note¹: the values in brackets are the local weight calculation results of each dimension performance evaluation index.

). Furthermore, the index system was optimized according to the expert survey results. By comprehensively representing the performance indicators of coal enterprises, the meaning of the sustainable development performance of coal enterprises was deeply analyzed, and the performance level of coal enterprises was comprehensively measured.

Firstly, financial performance indicators are mainly used to measure the profitability, solvency, operating capacity, and development capacity of coal enterprises. Profitability refers to the enterprise ‘s capital or capital appreciation ability, usually for a certain period of time in terms of the amount and level of profit. Debt-paying ability refers to the ability of enterprises to repay their debts, which is an important symbol reflecting the financial situation and operating ability of enterprises. Operating ability refers to the turnover operation ability of enterprise assets, which reflects the efficiency and quality of asset utilization. Development ability refers to the future business growth trend and development speed of enterprises, reflecting the future development prospect of the enterprises. Specifically, Return on equity (%) = net profit/average owner’s equity × 100%, Operating profit margin (%) = operating profit/operating revenue × 100%, Return on capital (%) = net profit/average capital × 100%, Quick ratio (%) = quick assets/current liabilities × 100 %, Cash flow liability ratio (%) = net operating cash flow/current liabilities at year-end × 100%, Asset–liability ratio (%) = total liabilities/total assets × 100 %, Total asset turnover rate (times) = total operating income/average total assets, Current assets turnover rate (times) = total operating income/average total current assets, Accounts receivable turnover ratio (times) = total operating income/average balance of accounts receivable, Growth rate of total operating income (%) = total operating income growth for this year/total operating income last year × 100%, Growth rate of operating profit (%) = (current year’s operating profit − last year’s operating profit)/last year’s operating profit × 100%, Growth rate of total assets (%) = (Total assets at the end of the year − total assets at the beginning of the year)/Total assets at the beginning of the year × 100%.

Secondly, environmental performance is used to analyze the environmental burden caused by the production and operation of coal enterprises, focusing on energy consumption, resource utilization, pollution control, and emission reduction. Energy consumption mainly measures the energy consumption of coal production, that is, the energy consumed by coal mining directly, the auxiliary production system without coal mining and other industrial production units of the enterprise. When it comes to resource utilization, natural resources are the foundation of the survival and development of coal enterprises. Whether the existing resources can be used to the maximum extent and whether the recycling and comprehensive utilization of resources can be realized is an important aspect of the environmental performance of coal enterprises. Pollution reduction is mainly used to measure sulfur dioxide, nitrogen oxide, chemical oxygen demand, ammonia nitrogen, and other emissions from coal mining and processing. Specifically, Comprehensive energy consumption of raw coal production (kg standard coal/ton coal) = total energy consumption of raw coal production in the year/raw coal production in the year, Recovery rate of mining area (%) = coal production in mining area/reserves of utilized coal resources in mining area, Utilization rate of coal gangue (%) = total utilization of coal gangue produced in the current year/total production of coal gangue in the current year, Mine water utilization rate (%) = annual total utilization of mine water/annual total production of mine water, Sulfur dioxide emission reduction rate (%) = (sulfur dioxide emission in current year − Sulfur dioxide emission in last year)/Sulfur dioxide emission in last year × 100%, Nitrogen oxide emission reduction rate (%) = (current year nitrogen oxide emission − last year nitrogen oxide emission)/last year nitrogen oxide emission × 100%, Chemical oxygen demand reduction rate (%) = (current year chemical oxygen demand emissions − last year chemical oxygen demand emissions)/last year chemical oxygen demand emissions × 100%.

Thirdly, social performance is used to measure the contribution of coal enterprises to society in the daily production and operation process and the impact on the daily life of the public, including enterprise scientific and technological innovation, employee rights and interests, safety responsibility, and social contribution level. Specifically, Ratio of R&D personnel (%) = Total number of R&D personnel/Total number of employees, Proportion of R&D expenditure (%) = R&D expenditure of the current year/total operating income of the current year, Cash ratio paid to employees (%) = cash paid to and for employees/cash received from selling goods and providing services × 100%, Employee per capita annual income growth rate (%) = (employee per capita annual income of current year − employee per capita annual income of last year)/employee per capita annual income of last year × 100%, Proportion of safety production input (%) = safety production cost/current total operating income × 100%, Coal production death rate per million tons (%) = number of deaths/actual production (million tons), Tax contribution rate (%) = tax paid/total operating income of the current period, Social contribution per share (yuan) = total social contribution/average value of total shares at the beginning and end of the period.

Fourthly, governance performance indicators are mainly used to measure the governance of shareholders, the governance of the board of directors, the governance of managers, and the governance of the board of supervisors. The shareholder governance performance of coal enterprises is expressed by Herfindahl_5 index and dividend distribution ratio index. Herfindahl_5 =${\displaystyle \sum }_{i=1}^{i=5}{S}_i^2, S_i$ represents the shares held by the ith largest shareholder. Dividend distribution ratio = dividend per share before tax/(net profit of the current period/paid-in capital value at the end of the current period) × 100%. The proportion of independent directors and the number of board meetings are selected to measure the board governance performance of coal enterprises. Proportion of independent directors = number of independent directors/total number of board of directors × 100%. Number of board meetings (times) = number of board meetings held during an accounting period. The proportion of executive compensation and management cost ratio are selected to measure the managers governance performance of coal enterprises. Proportion of executive compensation = total executive compensation in a certain accounting period/total profit in the current period × 100%. Management expenses ratio = management expenses of a certain accounting period/current primary business income × 100%. The number of board of supervisors’ meetings and the proportion of supervisors’ compensation are selected to measure the governance performance of the board of supervisors in coal enterprises. Number of meetings of the board of supervisors (times) = number of meetings of the board of supervisors held in an accounting period. Compensation proportion of supervisors = total compensation of supervisors in a certain accounting period/total profit of the current period × 100%.

4. Construction of Performance Evaluation Model of Coal Enterprise Based on Entropy Method and Cloud Model

4.1. Weight Assignment of Coal Enterprise Performance Evaluation Index Based on Entropy Method

The basic idea of the entropy method (EM) to determine the weight is to use the information entropy value to determine the dispersion degree of each index and then obtain the relatively objective weight through correction. In the comprehensive evaluation of quantitative index, compared with the principal component analysis method and other weight determination methods, the entropy method can avoid the influence of subjective factors on weight determination. The entropy method is suitable for evaluation of multiple time periods and different research objects [75] and has low requirements on data distribution. Therefore, we use the entropy method to determine the index weight.

$$X={\left[x_{ij}\right]}_{m\times n} (i=1,2,\dots \dots m;j=1,2,\dots \dots n)$$

(1)

In the second step, according to Formulas (2) and (3), the reverse indicators and moderate indicators in the index system are positively processed.

$$X_{ij}^{\prime }=\frac{1}{X_{ij}}$$

(2)

$$X_{ij}^{\prime }=\frac{1}{\mathrm{ABS}\left(X_{ij}-\overline{X_{ij}}\right)}$$

(3)

In the third step, the range method is used to standardize the original index $X_{ij}$ after normalized processing in the measurement system, and the standardized matrix $Y={\left[y_{ij}\right]}_{m\times n}$ is obtained.

$$Y_{ij}=\frac{X_{ij}-\min \left(X_{ij}\right)}{\max \left(X_{ij}\right)-\min \left(X_{ij}\right)}$$

(4)

Among them, $i=1,2,\dots ,\mathrm{m} ;j=1,2,\dots ,\mathrm{n}$; $Y_{ij},X_{ij},\underset{1<i<m}{\max }{X}_{ij},\underset{1<i<m}{\min }{X}_{ij}$ are the jth standard value, measured value, maximum value, and minimum value of the ith evaluation object, respectively. Since the value range of data processed by range method is 0~1, and the existence of zero value has no practical significance for entropy method, 0.000005 units of standardized data are selected to the right.

In the fourth step, according to the definition of information entropy, the proportion $P_{ij}$ of the jth index in the ith evaluation object in the process of entropy calculation can be obtained.

The fifth step is to calculate the information entropy $E_j$ of the jth index.

$$P_{ij}=\frac{y_{ij}}{{{\displaystyle \sum }}_{i=1}^{i=m}{y}_{ij}} ,i=1,2,\dots ,\mathrm{m} ;j=1,2,\dots ,\mathrm{n}$$

(5)

$$E_j=-\frac{1}{\ln m}\left\{{\displaystyle \sum }_{i=1}^{i=m}\left[\left(P_{ij}\right)\ln \left(P_{ij}\right)\right]\right\},i=1,2,\dots ,\mathrm{m} ;j=1,2,\dots ,\mathrm{n}$$

(6)

On the basis of a series of calculations above, the objective weight $W_j$ of the jth index can be determined.

$$W_j=\frac{1-E_j}{{{\displaystyle \sum }}_{j=1}^{j=n}\left(1-E_j\right)},j=1,2,\dots ,\mathrm{n}$$

(7)

4.2. Construction of Coal Enterprise Performance Evaluation Model Based on Cloud Model

Cloud model (CM) is an uncertain transformation model that deals with qualitative concepts and quantitative descriptions. It uses cloud generator to realize the transformation between qualitative concept and quantitative description. Fuzziness and randomness are considered in the transformation process, and the result can be presented in the form of a cloud map. Compared with traditional performance comprehensive evaluation methods such as fuzzy comprehensive evaluation method and Wohl’s score method, it is more objective, scientific, and intuitive.

4.2.1. Division of Index Grade

According to the characteristics of different indicators, different policy standards are selected as reference, and scientific and reasonable classification methods are adopted to classify the levels of each specific indicator. Further, the classification results are discussed with experts, and the final index grade is determined after the grade interval is optimized.

In this paper, the overall performance of coal enterprises is divided into five grades (excellent (A), good (B), medium (C), low (D), and poor (E)) according to the interim Measures for the Management of Comprehensive Performance Evaluation of Central Enterprises [76] and the Implementation Rules of Comprehensive Performance Evaluation of Central Enterprises [77]. Correspondingly, each specific index is also divided into the above five grades. For the grade division of specific indicators, the following principles should be followed: If the index has policy standard as reference, grade division is carried out on the basis of the reference value given by policy standard. If there is no policy standard and other relevant provisions, the expert experience method is adopted, and the index grade is divided after discussion with experts. In this paper, the performance evaluation index system of coal enterprises based on ESG is divided into four aspects: financial, environmental, social, and governance performance, which need to be divided into index levels according to the characteristics of different indicators.

Financial Performance Index

First, index grade nodes are determined. On the basis of the five grade standard values of excellent, good, average, low, and poor financial performance indicators of the whole coal industry published by the Appraisal and Distribution Bureau of the State−owned Assets Supervision and Administration Commission of the State Council, the average values of each two adjacent grades are calculated, and the calculated average values are used as four grade nodes to divide index grades: c1 = (excellent value + good value)/2, c2 = (good value + medium value)/2, c3 = (medium value + low value)/2, c4 = (low value + poor value)/2.

Secondly, the upper limit of excellent (A) grade and the lower limit of poor (E) grade should be determined to realize the grade cloud of the above indicators in the cloud model. By comparing the financial index values of listed companies in the coal industry in 2020, we determined the industry optimal value and the industry worst value of each index. Further, the optimal value of each index is the upper limit of the excellent (A) grade of each financial performance index, and the worst value of each index is the lower limit of the poor (E) grade of each financial performance index.

Therefore, the division intervals of the positive indicators of financial performance A, B, C, D, and E are as follows: $\left[{\mathrm{c}}_1,\mathrm{Upper} \mathrm{limit} \mathrm{of} \mathrm{index} \mathrm{value}\right]$, $\left.\left[{\mathrm{c}}_2\right.,{ \mathrm{c}}_1\right)$, $\left.\left[{\mathrm{c}}_3\right.,{ \mathrm{c}}_2\right)$, $\left.\left[{\mathrm{c}}_4\right.,{ \mathrm{c}}_3\right)$, $\left.\left[\mathrm{Lower} \mathrm{limit} \mathrm{of} \mathrm{index} \mathrm{value}\right.,{\mathrm{c}}_4\right)$; the division intervals of the reverse indicators of financial performance A, B, C, D, and E are as follows: $\left[\mathrm{Lower} \mathrm{limit} \mathrm{of} \mathrm{index} \mathrm{value},{\mathrm{c}}_1\right], \left({\mathrm{c}}_1,\right.\left.{\mathrm{c}}_2\right], \left({\mathrm{c}}_2,\right.\left.{\mathrm{c}}_3\right], \left({\mathrm{c}}_3,\right.\left.{\mathrm{c}}_4\right]$, $\left({\mathrm{c}}_4,\right.\left.\mathrm{Upper} \mathrm{limit} \mathrm{of} \mathrm{index} \mathrm{value}\right]$.

Environmental Performance Index

The environmental performance index system includes three dimensions: energy and resource consumption, comprehensive utilization of resources, and pollution control and emission reduction.

Among them, “Cleaner Production Evaluation Index System of Coal Mining and Separation Industry”, “Cleaner Production Standards-Coal Mining and Separation Industry”, “Coal Mining Unit Product Energy Consumption Quota”, “Interim Provisions on Coal Mining Recovery Rate Management”, “Opinions on Promoting Coal Safety and Green Development and Clean and Efficient Utilization”, and other standards and documents [78,79] divide the standard values of energy resource consumption indicators and resource comprehensive utilization indicators into three grades: grade I standard value, grade II standard value, and grade III standard value. The grade I standard value represents the international leading level value, the grade II standard value represents the domestic advanced level value, and the grade III standard value represents the domestic general level.

Therefore, for the positive/reverse indexes of energy and resource consumption and comprehensive utilization, the interval division principle is as follows. As for positive indexes, we take the above grade I standard value as the lower limit of excellent (A) grade and the upper limit of good (B) grade, the grade II standard value as the lower limit of good (B) grade and the upper limit of medium (C) grade, and the grade III standard value as the lower limit of medium (C) grade and the upper limit of low (D) grade. As for reverse indexes, we take the above grade I standard value as the upper limit of excellent (A) grade and the lower limit of good (B) grade, the grade II standard value as the upper limit of good (B) grade and the lower limit of medium (C) grade, and the grade III standard value as the upper limit of medium (C) grade and the lower limit of low (D) grade. The intervals of low (D) and poor (E) grades are determined successively with the intervals of the above defined grades as the standard.

On the basis of the comprehensive analysis of the current situation of pollution control and emission reduction in coal industry, the grade division of pollution control and emission reduction indicators is carried out by using the expert experience method.

Social Performance Index

First of all, we systematically analyzed some social responsibility report of listed coal companies in 2020. Moreover, we comprehensively analyzed the social responsibility performance of 23 listed companies in the coal industry in 2020. Moreover, the research results of the “Blue Book on Social Responsibility of Coal Industry (2021)” and “Social Responsibility Report of Listed Coal Companies (2021)” were referred to [80,81]. Furthermore, the industry optimal value, industry worst value, and industry average value corresponding to each social performance index were determined. The interval in which the index values were most concentrated was determined. Finally, on the basis of the results of discussion with experts, social performance indicators were classified.

Governance Performance Index

Firstly, we analyzed the Company Law, Securities Law, Listed Company Governance Code, and Listed Company Independent Director Rules. Furthermore, we analyzed the China Listed Company Governance Index (CCGI) (2021), China Listed Company Green Governance Index (CGGI) (2021), and corporate governance performance indicators of 23 listed companies in the coal industry in 2020. Moreover, the research results of the China Listed Company Governance Sub−Index Report (2021) were referred to [82]. On the basis of the above analysis, the industry optimal value, industry worst value, and industry average value corresponding to each governance performance index were determined. The interval in which the index values were most concentrated was determined. Secondly, we divided the levels of governance performance indicators on the basis of expert discussion.

To sum up, the index grade division results of financial performance, environmental performance, social performance, and environmental performance are shown in

Table 5. Final grade division results of all three-level indicators.

	Excellent (A)	Good (B)	Medium (C)	Low (D)	Poor (E)
C1-1	[9.05,12.08]	[5.30,9.05)	[1.55,5.30)	[−2.20,1.55)	[−5.95,−2.20)
C1-2	[15.30,21.62]	[8.96,15.30)	[2.63,8.96)	[−3.70,2.63)	[−10.03,−3.70)
C1-3	[14.90,20.90]	[8.90,14.90)	[2.90,8.90)	[−1.70,1.02)	[−4.42,−1.70)
C2-1	[95.90,119.15]	[72.65,95.90)	[49.4,72.65)	[26.15,49.40)	[2.90,26.15)
C2-2	[15.32,21.86]	[8.80,11.9)	[2.27,8.80)	[−8.80,2.27)	[−15.33,−8.80)
C2-3	[38.73,51.10]	(51.10,63.47]	(63.47,75.84]	(75.84,88.21]	(88.21,100.58]
C3-1	[0.64,0.77)	[0.51,0.64)	[0.38,0.51)	[0.25,0.38)	[0.12,0.25)
C3-2	[1.80,2.25)	[1.35,1.80)	[0.90,1.35)	[0.45,0.90)	[0.05,0.45)
C3-3	[12.99,16.67)	[9.31,12.99)	[5.63,9.31)	[1.95,5.63)	[0.05,1.95)
C4-1	[13.75,23.75)	[3.75,13.75)	[−6.25,3.75)	[−16.25,−6.25)	[−26.25,−16.25)
C4-2	[4.65,15.00]	[−5.70,4.65)	[−16.05,−5.70)	[−26.40,−16.05)	[−36.75,−26.40)
C4-3	[7.79,11.82]	[3.76,7.79)	[−0.27,3.76)	[−4.30,−0.27)	[−8.33,−4.30)
C5-1	[0.00,3.00]	(3.00,7.00]	(7.00,11.00]	(11.00,15.00]	(15.00,19.00]
C6-1	[90.00,100.00]	[80.00,90.00)	[70.00,80.00)	[60.00,70.00)	(50.00,60.00)
C6-2	[85.00,90.00]	[80.00,85.00)	[75.00,80.00)	[70.00,75.00)	[65.00,70.00)
C6-3-1	[95.00,100.00]	[90.00,95.00)	[85.00,90.00)	[80.00,85.00)	[75.00,80.00)
C6-3-2	[80.00,85.00]	[75.00,80.00)	[70.00,75.00)	[65.00,70.00)	[60.00,65.00)
C6-3-3	[70.00,75.00]	[65.00,70.00)	[60.00,65.00)	[55.00,60.00)	[50.00,55.00)
C7-1	[40.00,50.00]	[30.00,40.00)	[20.00,30.00)	[10.00,20.00)	[0.00,10.00)
C7-2	[40.00,50.00]	[30.00,40.00)	[20.00,30.00)	[10.00,20.00)	[0.00,10.00)
C7-3	[40.00,50.00]	[30.00,40.00)	[20.00,30.00)	[10.00,20.00)	[0.00,10.00)
C8-1	[9.00,13.00]	[5.00,9.00)	[1.00,5.00)	[0.05,1.00)	[0.00,0.05)
C8-2	[2.00,2.50]	[1.50,2.00)	[1.00,1.50)	[0.50,1.00)	[0.00,0.05)
C9-1	[20.00,25.00]	[15.00,20.00)	[10.00,15.00)	[5.00,10.00)	[0.00,5.00)
C9-2	[10.00,15.00]	[5.00,10.00)	[0.00,5.00)	[−5.00,0.00)	[−10.00,−5.00)
C10-1	[2.00,2.50]	[1.50,2.00)	[1.00,1.50)	[0.50,1.00)	[0.00,0.50)
C10-2	[0.00,0.05]	(0.05,0.10]	(0.10,0.15]	(0.15,0.20]	(0.20,0.25]
C11-1	[20.00,25.00]	[15.00,20.00)	[10.00,15.00)	[5.00,10.00)	[0.00,5.00)
C11-2	[4.00,5.00]	[3.00,4.00)	[2.00,3.00)	[1.00,2.00)	[0.00,1.00)
C12-1	[0.10,0.20]	(0.20,0.30]	(0.30,0.40]	(0.40,0.50]	(0.50,0.60]
C12-2	[70.00,90.00]	[50.00,70.00)	[30.00,50.00)	[10.00,30.00)	[0.00,10.00)
C13-1	[50.00,58.00)	[42.00,50.00)	[33.00,42.00)	[25.00,33.00)	[17.00,25.00)
C13-2	[14.00,17.00]	[11.00,14.00)	[8.00,11.00)	[5.00,8.00)	[2.00,5.00)
C14-1	[0.00,0.20]	(0.20,0.40]	(0.40,0.60]	(0.60,0.80]	(0.80,1.00]
C14-2	[0.00,3.00]	(3.00,6.00]	(6.00,9.00]	(9.00,12.00]	(12.00,15.00]
C15-1	[8.00,10.00]	[6.00,8.00)	[4.00,6.00)	[2.00,4.00)	[0.00,2.00)
C15-2	[0.00,0.04]	(0.04,0.08]	(0.08,0.12]	[0.12,0.16)	[0.16,0.20)

.

4.2.2. Normal Cloud Processing for Index Grade

According to the result of index grade division, the cloud model is further used to cloud the index grade. Three digital features Ex, En, and He of the index grade normal cloud are calculated, which lays a foundation for the next step of calculating the index grade membership degree.

It is assumed that the upper and lower limits of the grade $v_i$ corresponding to a certain index $C_i$ are $x_{ij}^1$ and $x_{ij}^2$, respectively. According to the formula, $E{x}_{ij}=\frac{x_{ij}^1+x_{ij}^2}{2}$, the qualitative concept of $v_i$ corresponding to $C_i$ can be expressed by the normal cloud model. $E_{x_{ij}}$ represents the expected value of the normal cloud model of grade $v_i$ corresponding to the quantitative indicator $C_i$. Since the upper and lower boundary values of the corresponding grade are critical values of transition from one grade to another, the index should belong to two grades at the same time, with certain fuzziness and equal membership degree. That is,

$$\exp \left[-\frac{{\left(x_{ij}^1-x_{ij}^2\right)}^2}{8{\left(E{n}_{ij}\right)}^2}\right]\approx 0.5$$

(8)

$$E{n}_{ij}=\frac{x_{ij}^1-x_{ij}^2}{2.355}$$

(9)

$E{n}_{ij}$ represents the entropy of the normal cloud model of grade $v_i$ corresponding to the quantitative indicator $C_i$.

Super entropy $H{e}_{ij}$ represents the measurement of entropy uncertainty, reflecting the condensation degree of cloud droplets. The smaller the super entropy value is, the smaller the cloud thickness is, and vice versa. Usually, $E{n}_{ij}$/$H{e}_{ij}$ > 10 is required. At this time, the absolute error of Ex is less than 0.01, the relative error of En is less than 2%, and the relative error of He is less than 10%. In this paper, after referring to the relevant literature and discussing with experts, we used $E{n}_{ij}$/$H{e}_{ij}$ = 20 to calculate the super entropy$H{e}_{ij}$.

According to the above definition, three numerical characteristics of the cloud model corresponding to the level $v_i$ of a certain index $C_i$ can be remembered as $C_{ij}\left(E{x}_{ij},E{n}_{ij},H{e}_{ij}\right)$. According to the same method to calculate the numerical characteristics of all the quantitative indexes, the grade standard matrix of quantitative indexes can be obtained: $C={\left[C_{ij}\left(E{x}_{ij},E{n}_{ij},H{e}_{ij}\right)\right]}_{q\times m}$. Further, the three numerical characteristics (Ex, En, He) of cloud corresponding to different grades of each index are calculated, as shown in Appendix A. We used MATLAB software to program and obtain the standard normal cloud diagram corresponding to each index. Taking “operating profit margin” as an example, its standard normal cloud diagram is shown in Figure 4. At the same time, the MATLAB code is given in the Attachment.

4.2.3. Membership Degree of Index Grade

On the basis of the standard normal cloud corresponding to each index grade, according to the X condition cloud generator, the membership degree of each grade corresponding to the quantitative index value $\mathrm{X}={\mathrm{X}}_0$ of the case company is calculated by using the formula ${\mu }_x=\exp \left[-\frac{{\left(x-Ex\right)}^2}{2E{n}^{’2}}\right]$. Moreover, the normalization process is carried out. The cloud generator is repeatedly run for N times to calculate the average comprehensive value of membership at all grades, so as to enhance the credibility of evaluation. Thus, the grade membership matrix of the whole index system can be obtained as $\mu ={\left({\mu }_{ij}\right)}_{n\times m}$.

4.2.4. Evaluation of Enterprise Performance Grade

The index weight $W=\left\{W_1,W_2,\dots ,W_n\right\}$ is multiplied by the grade membership matrix $\mu ={\left({\mu }_{ij}\right)}_{n\times m}$ of the index system. Then, the membership vector $R=W\times \mu =\left\{r_1,r_2,\dots ,r_n\right\}$ of coal enterprise performance level is obtained. Thus, the membership degrees at different grades of the evaluated coal enterprise performance are determined. According to the maximum membership principle or weighted membership principle to determine the performance grade.

Among them, the principle of maximum membership degree means that in the final membership degree matrix, the evaluation grade corresponding to the comprehensive index with the highest membership degree is set as the grade of the evaluation result. The principle of maximum membership degree does not have universality and has defects and ineffectiveness. Therefore, the validity of the principle should be considered before applying it [83,84]. The validity of the maximum membership principle is usually measured by $\alpha$ index, $\alpha =\frac{m\beta -1}{2\gamma \left(m-1\right)}$. In the formula, $\beta =\underset{1\le i\le m}{\max }\left\{r_i\right\}$ is the maximum membership value in $R=\left\{r_1,r_2,\dots ,r_n\right\}$. $\gamma =\underset{1\le i\le m,i\ne j}{\max }\left\{r_j\right\}$ is the second largest membership value in $R=\left\{r_1,r_2,\dots ,r_n\right\}$.

It is generally believed that the larger $\alpha$ is, the higher the validity of the maximum membership principle. $\alpha =+\infty$,the validity is excellent; $1\le \alpha <+\infty$, the validity is good; $0.5\le \alpha <1$, the validity is medium; $0.5\le \alpha <1$, the validity is low; $\alpha =0$, it is not valid at all.

Under the principle of weighted membership [84], the eigenvalue $j^{\ast }$ of the grade variable needs to be calculated. $j^{\ast }=\frac{{{\displaystyle \sum }}_{j=1}^{j=m}j\times r_j}{{{\displaystyle \sum }}_{j=1}^{j=m}{r}_j},j=1,2,3\dots ,m$. $j$ is the grade value, $m$ is the number of grades, and $r_j$ is the membership degree corresponding to $j$ grade. The characteristic value $j^{\ast }$ of the grade variable is closest to the quantitative value in the evaluation grade, then the evaluation result of the evaluated object is judged to be closest to this grade.

According to the construction process of performance evaluation index system, performance evaluation index weighting model, and performance evaluation model of coal enterprises, the ESG-GT-EM-CM model framework for performance evaluation of coal enterprises is formed, as shown in Figure 5.

5. Case Analysis of Coal Enterprise Performance Evaluation Based on ESG-GT-EM-CM

5.1. Research Object and Data Source

Enterprise Z is a large central energy enterprise integrating coal production and trade, the coal chemical industry, coal mine equipment manufacturing and related services, pithead power generation, and other businesses. Enterprise Z, led by the board of directors, establishes the ESG issue database and evaluates its importance. Then, key ESG issues are identified, and major ESG issues are considered and decided on. The original data required for the performance evaluation of enterprise Z based on ESG come from the China Stock Market and Accounting Research database, East Money network, HeXun network, the annual financial report, and the social responsibility report of enterprise Z from 2016 to 2020. After sorting everything out, the performance evaluation index system data of enterprise Z from 2016 to 2020 can be obtained.

5.2. Application of Performance Evaluation Model

5.2.1. Weight of Performance Evaluation Index

The weight value of enterprise Z performance evaluation index is determined by the entropy method. First of all, the original data of the enterprise Z performance evaluation index are standardized and forward processed by SPSS software to obtain standardized data. Secondly, on the basis of the standardized data, the entropy value is calculated by SPSS, and the entropy value, difference coefficient, and three−level index weight of each specific index are obtained. Finally, according to the calculation results of the entropy method, the weights of all third−level indexes belonging to the same second−level indexes are summarized. The weight of each secondary indexes is obtained in turn. Then, the weights of the second−level indexes belonging to the same first−level indexes are summarized, and the weights of the first−level indexes are obtained successively. The weights at all levels of the index system calculated on the basis of the entropy method are shown in Table 4.

5.2.2. Grade Membership Degree of Performance Evaluation Index

According to the formula ${\mu }_x=\exp \left[-\frac{{\left(x-Ex\right)}^2}{2E{n}^{\prime 2}}\right]$ and the standard matrix of quantitative index grade, X conditional cloud generator is used to calculate the membership degree of each grade corresponding to each performance index value of Z coal enterprise in 2016–2020 by MATLAB software. Since the result calculated by substituting the index value into the formula has certain randomness, when substituting the quantitative index value into the rank membership function, repeat calculation N=1000 times, and take the average membership degree of the index value belonging to different grades as the final rank membership degree. In particular, when the sample value of the positive index is higher than the average Ex of the boundary interval of the excellent grade (A) or lower than the average Ex of the boundary interval of the poor grade (E), the sample value of the reverse index is lower than the average Ex of the boundary interval of the excellent grade (A) or higher than the average Ex of the boundary interval of the poor grade (E), and the sample index belongs to the excellent grade (A) or the poor grade (E). That is, the membership degree of the sample index value belongs to the excellent (A) level or the poor (E) level is 1.

Here, we take the calculation of excellent grade (A) membership of Z enterprise’s operating profit rate in 2020 as an example. It is known that the three digital characteristics corresponding to the excellent grade (A) of this index are Ex = 18.460, En = 2.688, and He = 0.134. The operating profit rate of enterprise Z in 2020 is 8.74. It can be calculated by MATLAB software that the membership degree of the index value belonging to excellent (A) grade is 1.2645 × 10⁻⁶ (the MATLAB code is given in the attachment). Furthermore, by inputting Ex, En, and He corresponding to different levels of operating profit margin indexes in MATLAB software, the grade membership degree of operating profit margin indexes of enterprise Z from 2016 to 2020 is calculated and normalized at the same time.

Repeat the above steps to calculate the grade membership of other index values of enterprise Z and carry out normalization processing. Then, the membership degree of each performance index of enterprise Z in 2016–2020 is obtained. Due to limited space, only the membership matrix of specific index performance grade of Z coal enterprise in 2020 is given here, as shown in

Table 6. Z coal enterprise performance evaluation index grade membership matrix in 2020.

	Excellent (A)	Good (B)	Medium (C)	Low (D)	Poor (E)
C1-1 Return on equity(%)	0.0834	0.8913	0.0253	0.0000	0.0000
C1-2 Operating profit margin(%)	0.0014	0.4428	0.5529	0.0030	0.0000
C1-3 Return on capital(%)	0.0004	0.3954	0.6026	0.0017	0.0000
C2-1 Quick ratio(%)	0.0198	0.8347	0.1454	0.0002	0.0000
C2-2 Cash flow liability ratio(%)	1.0000	0.0000	0.0000	0.0000	0.0000
C2-3 Asset–liability ratio(%)	0.0862	0.8626	0.0512	0.0000	0.0000
C3-1 Total asset turnover rate (times)	0.0018	0.4960	0.5007	0.0015	0.0000
C3-2 Current assets turnover rate (times)	1.0000	0.0000	0.0000	0.0000	0.0000
C3-3 Accounts receivable turnover ratio (times)	1.0000	0.0000	0.0000	0.0000	0.0000
C4-1 Growth rate of total operating income (%)	0.0774	0.8947	0.0279	0.0000	0.0000
C4-2 Growth rate of operating profit(%)	0.2531	0.7406	0.0062	0.0000	0.0000
C4-3 Growth rate of total assets(%)	0.0002	0.3909	0.6046	0.0043	0.0000
C5-1 Comprehensive energy consumption of raw coal production (kg standard coal/ton coal)	0.0844	0.8853	0.0303	0.0000	0.0000
C6-1 Recovery rate of mining area(%)	0.4018	0.5859	0.0123	0.0000	0.0000
C6-2 Utilization rate of coal gangue(%)	1.0000	0.0000	0.0000	0.0000	0.0000
C6-3 Mine water utilization rate(%)	1.0000	0.0000	0.0000	0.0000	0.0000
C7-1 Sulfur dioxide emission reduction rate(%)	0.0000	0.0000	0.0006	0.3411	0.6583
C7-2 Nitrogen oxide emission reduction rate(%)	0.0000	0.0000	0.0000	0.0000	1.0000
C7-3 Chemical oxygen demand reduction rate(%)	1.0000	0.0000	0.0000	0.0000	0.0000
C8-1 Proportion of R&D personnel(%)	0.0217	0.9102	0.0672	0.0006	0.0004
C8-2 Proportion of R&D expenditure(%)	0.2189	0.7697	0.0114	0.0000	0.0000
C9-1 Cash ratio paid to employees(%)	0.0000	0.0000	0.0031	0.5460	0.4509
C9-2 Employee per capita annual income growth rate(%)	0.0001	0.0662	0.8610	0.0727	0.0000
C10-1 Proportion of safety production input(%)	0.0035	0.6053	0.3898	0.0014	0.0000
C10-2 Coal production death rate per million ton(%)	1.0000	0.0000	0.0000	0.0000	0.0000
C11-1 Tax contribution rate(%)	0.0000	0.0006	0.2809	0.7054	0.0130
C11-2 Social contribution per share (yuan)	0.0001	0.1483	0.8195	0.0321	0.0000
C12-1 Herfindahl_5 index	0.0000	0.0003	0.2396	0.7455	0.0145
C12-2 Dividend distribution ratio(%)	0.0000	0.0000	0.0400	0.9589	0.0011
C13-1 Proportion of independent directors(%)	0.0000	0.0380	0.9230	0.0390	0.0000
C13-2 Number of board meetings (times)	0.0000	0.0000	0.0001	0.1513	0.8486
C14-1 Proportion of executive compensation(%)	1.0000	0.0000	0.0000	0.0000	0.0000
C14-2 Management expenses ratio(%)	0.6618	0.3379	0.0003	0.0000	0.0000
C15-1 Number of meetings of the board of supervisors (times)	0.0000	0.0039	0.5128	0.4812	0.0021
C15-2 Compensation proportion of supervisors (%)	1.0000	0.0000	0.0000	0.0000	0.0000

. Please refer to the Appendix B for the membership matrix of enterprise Z performance indexes from 2016 to 2019.

5.2.3. Evaluation of Performance Levels

According to the calculation results of the membership degree of each index and grade of enterprise Z in each year, it can be seen that there was little difference between the membership degree of many indexes and grade. The principle of maximum membership degree is inefficient or even completely ineffective. Therefore, we used the weighted membership principle to evaluate the performance level. Numerical values 1–5 were used to correspond to quantitative values of five grades: excellent (A), good (B), medium (C), low (D), and poor (E). The average values of two adjacent grades were calculated, and the calculated average values were used as the four grade nodes 1.5, 2.5, 3.5, and 4.5 to classify characteristic values $j^{\ast }$. The performance level variable characteristic value of $j^{\ast }$ is calculated on the basis of the formula of $j^{\ast }=\frac{{{\displaystyle \sum }}_{j=1}^{j=m}j\times r_j}{{{\displaystyle \sum }}_{j=1}^{j=m}{r}_j}.$ When $j^{\ast }$ is between 1 and 1.5, the performance of the evaluated object belongs to the excellent (A) grade. When$j^{\ast }$ is between 1.5 and 2.5, the performance of the evaluated object belongs to the good (B) grade. When $j^{\ast }$ is between 2.5 and 3.5, the performance of the evaluated object belongs to the medium (C) grade. When $j^{\ast }$ is between 3.5 and 4.5, the performance of the evaluated object belongs to the low (D) grade. When$j^{\ast }$ is between 4.5 and 5, the performance of the evaluated object belongs to the poor (E) grade. According to the coal enterprise performance evaluation model, the overall performance level of Enterprise Z and the specific performance level of the four dimensions of finance, environment, society, and governance are evaluated as follows. Due to limited space, only the final calculation results of characteristic values of performance−grade variables under the weighted membership principle are given here.

Evaluation of Overall Performance Level

By multiplying the three−level index grade membership degree of enterprise Z from 2016 to 2020 with the overall weight of each third−level index, the third−level index grade membership degree considering the index weight was calculated. According to the calculation results of the membership degree of each three−level index, further summarizing, and summing up, the grade membership of the overall performance of enterprise Z from 2016 to 2020 was finally obtained. At the same time, the characteristic value $j^{\ast }$ of the performance−grade variable for each year was calculated. The calculation results of the characteristic values of the overall performance grade variables in 2016−2020 are shown in Figure 6, and the grades are judged according to the weighted membership principle.

Evaluation of Specific Performance Level

Here, we take the evaluation of financial performance level as an example. First, the local weights of second−level indexes and third−level indexes in the financial performance dimension were calculated. The membership degree of each index grade was multiplied by its corresponding local index weight, and the membership degree of each third−level index considering the index weight in this dimension was calculated. By further summarizing and summing up, the membership degree of each secondary index level under the financial performance dimension of Z coal enterprise in 2016−2020 was obtained. Secondly, the membership degree of each second−level index grade was multiplied by the corresponding local weight of the second−level index, and the membership degree of each second−level index grade after considering the local weight was calculated. After that, the financial performance−grade membership degree of enterprise Z from 2016 to 2020 was obtained by summarizing and summing. Finally, the characteristic value $j^{\ast }$ of performance-grade variables corresponding to each year was calculated, and its performance grade was judged according to the weighted membership principle.

The evaluation process of environmental performance, social performance, and governance performance was consistent with that of financial performance. The local weight calculation results of each dimension performance are shown in Table 4. The evaluation results of the overall performance of each dimension and the performance of the second level indexes are shown in Figure 7, Figure 8, Figure 9 and Figure 10.

5.3. Analysis of Performance Evaluation Results

5.3.1. Overall Performance

From the perspective of performance level, the overall performance level of Z coal enterprise from 2016 to 2018 and 2020 is in the medium (C) grade, and the overall performance level in 2019 is in the good (B) grade. From the change trend of performance grade, the overall performance level declined slightly from 2016 to 2017, continued to rise from 2017 to 2019, and then declined slightly in 2020. The decline of overall performance in 2017 was mainly related to the decline of environmental performance and social performance. The decline again in 2020 was mainly due to the severe impact of the COVID-19 epidemic in 2020, and the coal industry saw a significant decline in profits in 2020. Under this background, enterprise Z has taken a series of measures in 2020, such as comprehensively promoting epidemic prevention and control, rapidly promoting rework and reproduction, and improving production efficiency. In 2020, enterprise Z achieved loss reduction and profit increase while ensuring energy supply, and its financial performance only decreased slightly, still maintaining a good level. However, at the same time, its investment in environmental responsibility, social responsibility, and corporate governance has been reduced, resulting in a slight decline in environmental performance, social performance, and governance performance. As a result, the overall performance of enterprise Z declined slightly in 2020. With the stabilization of the epidemic, enterprise Z should continue to be guided by the new energy security strategy and the “2030·2060” carbon peak and carbon neutral energy development goals. While maintaining high financial performance, focus is required on improving environmental performance, social performance, and governance performance, as well as enhancing the performance of sustainable development.

5.3.2. Financial Performance

Macro Perspective

From the perspective of performance level, the financial performance level of enterprise Z in 2016 is in the medium (C) level, and the financial performance level in 2017–2020 is in the good (B) level. From the perspective of the change trend of performance level, the financial performance level of enterprise Z has been on the rise as a whole, and the financial performance is good and is gradually tending towards being excellent. Among them, the financial performance level in 2018–2019 increased by a small margin, mainly affected by the sluggish development of the coal industry in 2019. In 2019, coal demand decreased, the coal market has a serious oversupply problem, and the overall market is not optimistic. In 2020, due to the impact of the epidemic, the pressure on the production and operation of coal enterprises increased sharply. On this background, the financial performance level of enterprise Z only showed a slight decline compared with 2019, and even the scale of coal production and sales and operating income both reached a record high. This reflects Z enterprise’s strong economic strength, excellent overall management ability, and risk response ability.

Micro Perspective

In terms of profitability, Z enterprise’s profitability was in the medium (C) level from 2016 to 2018 and rose to the good (B) level in 2019. Its profitability declined slightly in 2020 but remained in a good (B) grade. This was mainly because of the impact of the COVID-19 epidemic and the adverse impact of the coal market environment, wherein its operating profit margin declined significantly. Enterprise Z should strengthen cost control, improve operating profit margin, and improve profitability while improving operating revenue.

In terms of debt-paying ability, Z enterprise’s debt-paying ability has been in the good (B) level from 2016 to 2020, indicating that it has good debt-paying ability, but there is still a certain gap from the excellent level. In 2019, the performance level of the enterprise’s debt-paying ability declined sharply, mainly because the enterprise borrowed heavily in 2019, resulting in a high debt level of current assets and weak debt-paying ability. However, in 2020, enterprise Z adjusted the scale and structure of debt, and its debt-paying ability was improved.

In terms of operating ability, the operating ability of enterprise Z was at a low (D) level in 2016, medium (C) level in 2017, good (B) level in 2018–2020, and very close to excellent (A) level in 2020. The asset quality of enterprise Z has been greatly improved in 5 years. This shows that enterprise Z has a strong operating ability, and its operating assets have higher efficiency and better benefits. Asset operating status, asset structure, and asset effectiveness are all at a good or even excellent level.

In terms of development ability, the development ability of enterprise Z in 2016 and 2020 was at the level of good (B), and the development ability from 2017 to 2019 was at the level of excellent (A). Enterprise Z has strong development potential. However, due to the impact of COVID-19 in 2020, the operating revenue and operating profit of enterprise Z decreased significantly. As a result, the growth rate of operating revenue and operating profit of enterprise Z decreased, and its development ability decreased from excellent (A) to good (B). In the future, enterprise Z should continue to improve its operating profit growth rate and appropriately expand the scale of assets, enhance the development potential of the enterprise, and reverse the downward trend of development ability.

5.3.3. Environmental Performance

Macro Perspective

From the perspective of performance level, enterprise Z was in the good (B) grade in 2016 and 2018–2020, and in 2017, it was in the medium (C) grade, but it was very close to the good (B) grade. From the perspective of performance change trend, the environmental performance of enterprise Z fluctuated greatly from 2016 to 2020 and decreased significantly from 2016 to 2017. The environmental performance of enterprise Z increased from 2017 to 2019 but decreased again from 2019 to 2020. This shows that the environmental performance level of enterprise Z fluctuates greatly and is not stable, which is mainly related to the intensity of environmental protection measures taken every year. In 2017, Z enterprise’s investment in environmental protection was relatively low, and the environmental protection measures taken were relatively small. Since 2018, it has vigorously promoted scientific mining methods, efficient resource utilization, clean production process, and an ecological mining environment. Good achievements have been made in pollution control, emission reduction, and resource and energy conservation, and environmental performance has been continuously improved. However, in 2020, due to the impact of COVID-19 and the coal market downturn, Z enterprise invested a large amount of capital in scientific production organization, improving the marketing system and carrying out economic activities such as improving quality and efficiency. As a result, investment in environmental responsibility declined, especially in pollution control and emission reduction, leading to a sharp decline in overall environmental performance in 2020.

Micro Perspective

In terms of energy consumption, enterprise Z maintained a good grade (B) in 2016–2020, with little difference in performance level each year. The comprehensive energy consumption of raw coal production has been in the advanced level of the domestic coal industry, but there is still a certain distance from the international leading level. It should continue to adhere to the principle of saving first, strengthening the publicity of energy saving, popularizing the concept of energy saving and low-carbon and innovate energy saving technology, and striving to ensure the normal production and operation activities with as little energy consumption as possible. In terms of resource utilization, enterprise Z was in the excellent (A) level in 2016, 2019, and 2020, and in the good (B) level in 2017 and 2018. On the whole, its resource utilization performance is excellent, and the recovery rate and utilization rate of coal gangue have been kept at the leading level of the industry. The reason for the sharp decline in resource utilization performance in 2017 was that the newly built coal mine was put into production in that year. The reason for the sharp decline in resource utilization performance in 2017 was that the production of new coal mines in the year was included in the statistics. The newly built coal mine has a large inflow of water; the mine water generated by enterprise Z increased by 150% year-on-year, and the mine water conservancy consumption increased by 93% year-on-year, resulting in a significant decrease in the utilization rate of mine water, from 79.6% in 2016 to 61.2% in 2017.

In terms of pollution control and emission reduction, enterprise Z was in medium (C) grade in 2016 and 2017, low (D) grade in 2018 and 2020, and good (B) grade in 2019. The performance of pollution control and emission reduction fluctuates greatly, and the overall performance is lower than the industry average. In the national “carbon peak” and “carbon neutral” decision deployment, enterprise Z should further improve the emission reduction rate of pollutants. At the same time, enterprise Z should strive to improve the ability of carbon emission control, strengthen source control, adhere to clean production and end governance, reduce greenhouse gas emissions, and improve the effect of pollution control and emission reduction.

5.3.4. Social Performance

Macro Perspective

From the perspective of performance level, Z enterprise’s social performance level from 2016 to 2020 was all in the medium (C) level. From the perspective of performance change trend, the social performance level decreased from 2016 to 2017 and recovered from 2017 to 2019, but the social performance level of enterprise Z declined again in 2020. The main reason was the decline of employee equity performance and social contribution performance. Specifically, the annual per capita income growth rate of employees has the largest decline. Among them, the per capita annual income growth rate of employees has the largest decline. In general, the social performance of enterprise Z has been in the middle level of the industry and has a trend of continuous decline. Social responsibility is an important aspect of the sustainable development ability of enterprises, and social responsibility performance is an important indicator to measure the sustainable performance of enterprises. Therefore, enterprise Z should increase investment in social responsibility, integrate social responsibility into corporate strategy, carry out social responsibility training, promote social responsibility practice, strengthen social responsibility communication, and effectively improve social responsibility performance.

Micro Perspective

In terms of technological innovation, enterprise Z was in the medium (C) level from 2016 to 2018 and in the good (B) level from 2019 to 2020, with an overall upward trend in technological innovation capability. During the five years from 2016 to 2020, the proportion of R&D personnel increased year by year, and the proportion of R&D investment increased year by year, except for 2018. This shows that enterprise Z attaches increasingly more importance to scientific and technological innovation, and accordingly, its scientific and technological research and development ability has been significantly enhanced, and many innovative achievements have been achieved.

In terms of employee rights, enterprise Z was in medium (C) grade in 2016, 2018, and 2019, and low (D) grade in 2017 and 2020. Overall, the performance of employee rights and interests in enterprise Z is poor, lower than the average level of the industry. However, employees are the foundation of an enterprise and are closely related to its development. Only by adhering to the people-oriented responsibility concept can an enterprise achieve sustainable development. Therefore, enterprise Z should focus on improving employee equity performance by optimizing income distribution structure and improving employee income level.

In terms of safety responsibilities, enterprise Z was in excellent (A) grade in 2016 and 2017 and good (B) grade in 2018–2020. In general, enterprise Z has excellent performance in safety responsibility. From 2016 to 2020, although the proportion of safety production input of enterprise Z decreased, the overall safety production input of enterprise Z showed a significant upward trend. Higher safety production input creates a good safety production environment for miners. The mortality rate of one million tons in enterprise Z from 2016 to 2020 was far lower than the average level of coal mines in China, and there was no death rate for three consecutive years from 2018 to 2020. Its safety risk has been effectively resolved.

In terms of social contribution, enterprise Z was in the low (D) grade in 2016 and medium (C) grade in 2017–2020, and its social contribution performance was in the medium level of the industry. From 2016 to 2020, the tax contribution rate of enterprise Z was stable at about 10%, which is the average level in the coal industry, but showed a downward trend. Its social contribution per share is generally on the rise, but there is still a large gap from the good and excellent level of the industry. Therefore, enterprise Z should use its own capital, manpower and technology to actively participate in local economic construction and boost local industrial upgrading and economic development, further increasing the total amount of social contribution and improving their own social contribution performance level.

5.3.5. Governance Performance

Macro Perspective

From the perspective of performance level, Z enterprise’s governance performance from 2016 to 2020 was all in the middle (C) grade. From the perspective of performance change trend, the level of governance performance declined from 2016 to 2018, picked up in 2019, but declined again in 2020. The decline of corporate governance is related to the decline of shareholder governance, board of directors governance, and board of supervisors governance. Therefore, enterprise Z should further improve the corporate governance structure composed of the general meeting of shareholders, the board of directors, the board of supervisors, and the management layer, and further clarify the rights and obligations of shareholders, the board of directors, the board of supervisors, and the managers, promoting enterprise reform and development from the corporate governance level and then effectively enhancing the enterprise’s core competitiveness and sustainable development ability.

Micro Perspective

In terms of shareholder governance, the shareholder governance performance of enterprise Z from 2016 to 2020 was in the low (D) grade, with poor shareholder governance performance. This was related to the high concentration of equity in enterprise Z, and the proportion of the largest shareholder of enterprise Z in the five years from 2016 to 2020 was 57.36%. However, “one dominant share” will damage the rights and interests of minority shareholders and adversely affect the performance of shareholder governance. Therefore, enterprise Z should dilute the shares of major shareholders and maintain a reasonable shareholding structure by issuing additional shares.

In terms of board governance, enterprise Z was in the low (D) grade in 2016, 2018, and 2020, and in the medium (C) grade in 2017 and 2019, but not much different from the low (D) grade. Independent directors account for one-third of the board of directors of enterprise Z, which is independent to a certain extent, but the number of board meetings is less. In the future, the number of board meetings should be increased to strengthen scientific decision making and supervision of the enterprise’s development strategy, investment plan, financial management, production and operation, and other major issues through board meetings.

In terms of managers governance, enterprise Z was in the grade of good (B) in 2016 and was excellent (A) in 2017–2020, and has been on the rise. This indicates that the managers governance level of enterprise Z is relatively high, the compensation incentives of managers are appropriate, and the governance cost is well controlled.

In terms of board of supervisors governance, enterprise Z was in the middle (C) level from 2016 to 2020, showing a downward trend on the whole, only rising from 2018 to 2019. This was mainly related to the smaller size of the board of supervisors, the fewer times of the board of supervisors’ meetings, and the insufficient incentive to the supervisors. However, the board of supervisors is the basis of internal control, so attention should be paid to the construction of the board of supervisors to promote the improvement of enterprise internal control mechanism.

5.4. Verification and Comparison of Results

In order to verify the ESG-GT-EM-CM model framework of coal enterprise performance evaluation constructed in this paper, enterprise Z was taken as an example for case analysis. We calculated the overall performance of enterprise Z from 2016 to 2020 and the performance level of each dimension, and conducted analysis from the macro and micro perspectives. The results showed that the financial performance and environmental performance of enterprise Z were good from 2016 to 2020, but the social performance and governance performance need to be further improved. The case analysis results are consistent with the reality of enterprise Z and the current situation of the industry, which further verifies the scientificality and feasibility of the ESG-GT-EM-CM model framework of coal enterprise performance evaluation constructed in this paper.

Static Analysis and Verification

Overall, from 2016 to 2020, the overall performance, financial performance, environmental performance, social performance, and governance performance of enterprise Z were medium or good. Financial performance and environmental performance, except for some years, were all good grades; the performance grades of social performance and governance performance over the years were all medium (

Table 7. Performance grade measurement results.

Time	Overall Performance	Financial Performance	Environmental Performance	Social Performance	Governance Performance
2016	medium	medium	good	medium	medium
2017	medium	good	medium	medium	medium
2018	medium	good	good	medium	medium
2019	good	good	good	medium	medium
2020	medium	good	good	medium	medium

). The level of financial performance and environmental performance of enterprise Z is higher than that of social performance and governance performance. By analyzing the original data of the indicators, we can see that the performance grade measurement results were consistent with the overall development status of enterprise Z. This verifies the scientificality and rationality of using the ESG-GT-EM-CM model framework to carry out performance evaluation of coal enterprises.

Dynamic Analysis and Comparison

On the basis of the performance grade measurement results and the real data of enterprise Z, the following comparison and analysis were made from the perspective of dynamic change trend: (1) From 2016 to 2020, the financial performance level of enterprise Z was on the rise on the whole, with good financial performance and gradually becoming excellent. This is consistent with the strong comprehensive economic strength of enterprise Z. (2) From 2016 to 2020, the environmental performance of enterprise Z fluctuated greatly. The level of environmental performance decreased significantly from 2016 to 2017 and increased from 2017 to 2019. However, the level of environmental performance decreased again in 2019–2020. This is consistent with the environmental protection measures and policies taken by enterprise Z every year. (3) From 2016 to 2017, the social performance level of enterprise Z decreased, and from 2017 to 2019, the social performance level of enterprise Z increased, but the social performance level of enterprise Z decreased again in 2020. This is consistent with the low ranking of Z enterprise’s social responsibility level in the industry. (4) From 2016 to 2018, the governance performance level of enterprise Z decreased, picked up in 2019, but declined again in 2020. The decline of corporate governance level of enterprise Z is consistent with the decline of governance level of shareholders, board of directors, and board of supervisors.

In addition, according to the measurement results of each three−level performance, it can be seen that its impact on the performance of the second−level index is consistent with its weight. This verifies the rationality of index weighting model in the model framework of ESG-GT-EM-CM.

6. Conclusions and Suggestions

6.1. Main Conclusions

On the basis of the ESG-GT-EM-CM model framework, the performance evaluation of coal enterprises was studied. The following conclusions were drawn through theoretical mechanism analysis, model construction, and case research.

6.1.1. Perspective of Theoretical Mechanism

On the basis of the concept ESG and the grounded theory, the structural dimension model and the index system of coal enterprise performance evaluation were constructed. From the four dimensions of finance, environment, society, and governance, a coal enterprise performance evaluation index system with 35 specific indicators was constructed. The index system is scientific, comprehensive, and feasible, which reflects the requirements of sustainable development and the characteristics of coal enterprises and can scientifically and objectively measure the sustainable development performance of coal enterprises.

6.1.2. Perspective of Model and Method

The performance evaluation model of coal enterprise based on ESG was constructed using the entropy method and cloud model. First, on the basis of constructing the performance evaluation index system, the entropy method was used to calculate the index weight. Second, according to the standards of relevant documents, the performance of coal enterprises was divided into five grades, namely, excellent (A), good (B), medium (C), low (D), and poor (E), and the interval of each specific index and each grade was determined. Third, the cloud model was used to carry out normal cloud processing for each index grade, and then the membership degree of each index grade was calculated. Finally, according to the principle of weighted membership degree, combined with the calculation results of index weight and grade membership degree, the performance of coal enterprises as a whole and in each dimension was evaluated.

6.1.3. Perspective of Case Analysis

First, taking enterprise Z as an example, on the basis of the constructed performance evaluation model of coal enterprises, the overall performance and the performance levels of various dimensions (financial performance, environmental performance, social performance, and governance performance) of enterprise Z from 2016 to 2020 were measured. Then, on the basis of the measurement results of performance level, the macro and micro analyses were carried out, and the shortcomings of enterprise Z in the development process were pointed out. In view of these shortcomings, corresponding countermeasures were proposed to help them further improve their sustainable development ability and improve the performance level of sustainable development.

6.2. Policy Implications

The above research shows that government departments and managers of coal enterprises should pay more attention to the sustainable development of coal enterprises. Government departments should intensify the transformation of the coal industry, uphold the concept of sustainable development, strengthen the supervision of coal enterprises, and formulate a perfect industry management system. Enterprises should continue to innovate, improve the technical level, rely on technological innovation to improve the comprehensive benefits of coal enterprises, and promote the intelligent development of coal enterprises. On this basis, the policy implications of this research are described below.

6.2.1. Optimization of Development Concept—Promoting Sustainable Development of Coal Enterprises

Overall, adherence is required towards the concept of sustainable development of the coal economy in order to obtain more ideal economic and social benefits. The coal industry is the primary pillar industry in China, closely associated with other industries, and we must actively take the road of sustainable development. However, the level of sustainable development of the coal industry has a large space for improvement, which requires the government, coal enterprises, and relevant departments to collaboratively govern the sustainable development problem of the coal economy.

Specifically, first of all, from the macro perspective, we should adhere to sustainable development, adjust the coal industry structure, and improve the proportion of coal energy clean production. In order to improve the comprehensive benefits of the coal economy, we should strengthen industry supervision, improve the technical standards of the coal industry, and establish a new pattern of sustainable and high-quality development of the coal economy. Secondly, from the micro perspective, we should pay more attention to the concept of sustainable development, strengthen the continuous improvement of the industry supervision system; improve the technical level of coal mining, tunneling, mechanical and electrical engineering, transportation, and ventilation; and optimize the management level of coal resources allocation.

6.2.2. Optimization of Development Mechanism—Improving the ESG Rating Level of Coal Enterprises

Here, we discuss improving the ESG rating level of coal enterprises. As the downstream industries of the coal industry are often characterized by high pollution, high emissions, and high energy consumption, they are prone to negative events, such as safety accidents and pollution discharge violations. Therefore, the rating level of coal enterprises in all kinds of ESG rating agencies is generally low, and some large global asset management institutions even exclude the coal industry in actual ESG investment [60]. From the subject of government, first, the mandatory ESG information disclosure system should be established and improved to guide enterprises to make substantial disclosure of ESG information. Second, we should strongly encourage the development of local ESG credit rating agencies and provide professional ESG consulting services for the market. From the subject of enterprise, first, improving ESG performance should be viewed as a “value investment” rather than simply a “cost input”, establishing an effective ESG management mechanism from the enterprise strategy level and improving the awareness of information disclosure of ESG. Second, it is necessary to increase efforts to improve the transparency of social responsibility information; implement systematic construction; and increase investment in technological innovation, environmental protection, and intelligent construction. Third, we should focus on reducing pollution and energy consumption, improving the safety and health of employees, so as to reduce or even eliminate the occurrence and fermentation of negative events. At the same time, coal enterprises need to improve their green technology innovation level, enabling the country to achieve carbon peak and carbon neutrality.

6.2.3. Optimization of Development Mode—Improving the Comprehensive Performance of Coal Enterprises

Improvement of sustainable development performance is necessary while maintaining high financial performance, focusing on improving environmental performance, social performance, and governance performance.

In terms of financial performance, first, the cost control should be strengthened, and operating profit margin and profitability should be improved. Second, the scale and structure of debt issuance should be optimized, and the solvency of coal enterprises should be improved. Third, the efficiency of operating assets should be improved, and the status and structure of assets should be optimized. Fourth, the scale of assets should be appropriately expanded, the development potential of enterprises should be enhanced, and the development capacity of enterprises should be improved.

In terms of environmental performance, first, one should adhere to the principle of giving priority to saving, increasing energy conservation publicity, popularizing energy-saving and low-carbon ideas, and innovating energy-saving technologies. Second, efforts should be made in terms of the mining area recovery rate and coal gangue utilization rate and other green indicators maintained at the leading level of the industry. Third, there should be a focus on improving carbon emissions control capabilities, strengthening source control, and adhering to cleaner production and end-of-pipe governance.

In terms of social performance, attention should be paid to integrating social responsibility into corporate strategy, carrying out social responsibility training, promoting social responsibility practice, strengthening social responsibility communication, and effectively improving social responsibility performance.

In terms of governance performance, we should improve the corporate governance structure and clarify the rights and obligations of shareholders, the board of directors, the board of supervisors, and managers. We should establish a mechanism of coordination and checks and balances among organs of power, decision making, supervision, and management with clear rights and responsibilities and standardized operation, effectively enhancing the enterprise’s core competitiveness and sustainable development ability.

6.2.4. Analysis of Management Countermeasures of Coal Enterprise Development from the Perspective of Sustainable Development

On the Basis of the Dimension of Financial Performance

With the continuous expansion of economic scale, the consumption of coal resources is also increasing, which brings about a series of problems such as environmental pollution and ecological destruction. Therefore, coal enterprises should adhere to green development in the process of development in order to promote the sustainable development of coal enterprises with low-carbon economic mode, improve the development quality of coal enterprises, and adapt to the needs of high-quality economic development and transformation [85].

First, the government makes policies. Government departments should scientifically and reasonably formulate measures to adjust the structure of the coal industry, carry out clean production of coal energy, improve production efficiency, and strengthen industry supervision, actively solving the economic development problems of the coal industry and providing a guarantee for improving financial performance. Second, enterprises respond to policies. Coal enterprises should actively respond to the supply-side structural reform and other macro policies to enable the optimal allocation of coal resources. At the same time, coal enterprises should fully conduct market research, grasp the market trends in a timely manner, and provide coal products more in line with market demand. Third, enterprises should upgrade their scientific and technological level. Coal enterprises should formulate management policies for scientific and technological innovation and increase investment in science and technology. For example, the exploitation method should be gradually improved and perfected to increase the collection and utilization rate of coalbed methane, promoting the integrated operation mode of coal, electricity, road, port, and chemical industries and maximizing the comprehensive utilization rate of coal resources.

On the Basis of the Dimension of Environmental Performance

First, coal enterprises should establish the consciousness of environmental protection and consciously implement the concept of sustainable development on the basis of green production and environmental protection [86]. Coal industry association and relevant government departments should play a leading and guiding role. Second, coal enterprises should make use of advanced science and technology, formulate management policies to promote the effective combination of coal production and the application of science and technology, and reduce the environmental pollution caused by coal mining. While improving the quality of coal mining, the efficiency of coal production should be improved. In addition, tax is an important factor to measure the sustainable development of coal enterprises. Government departments should formulate different tax policies according to the development mode of coal enterprises. For example, appropriate tax reductions should be made for coal enterprises with sustainable and high-quality development. However, tax should be increased for coal enterprises that pollute the production environment, waste serious resources, and have imperfect treatment.

On the Basis of the Dimension of Social Performance

If the government supervision and management system is not strict enough, coal enterprises will use coal resources in an extensive way, which will easily cause a large amount of resource waste and hinder the sustainable and high-quality development of coal enterprises [87].

First, policy guidance should be strengthened. Government departments should guide the sustainable and high-quality development of coal enterprises through macro policies, formulate reasonable and effective industry management systems, and standardize the rules and regulations in the production and management of coal enterprises. Second, supervision should be strengthened. Government departments should strengthen the supervision of coal enterprises, illegal coal enterprises should be banned according to law, illegal staff should be severely punished, and a sound industry supervision system should be established. In particular, we should strengthen the supervision of illegal mining of coal resources and realize the orderly macro-control and management of coal resources. Third, the allocation of resources should be optimized. Government departments should speed up the establishment and improvement of the supervision system, strengthen the supervision of coal enterprises, formulate and implement fine management policies, and gradually improve the management and allocation level of coal resources. For the regions with rich coal resources, the fine management mode should be carried out to reduce the waste of coal resources. For regions lacking coal reserves, supply-side structural reform should be carried out to optimize the existing industrial structure of the coal industry to make up for the shortage of coal resources and reserves.

On the Basis of the Dimension of Governance Performance

Advanced human resources are the priority of improving the management system. To optimize the industry management system and improve the corporate governance structure of coal enterprises, it is necessary to have a basis in the development demand of the market. In addition, we should combine with the development of the enterprise, formulate a perfect personnel welfare system, and improve salaries, so as to attract more advanced human resources.

On the Basis of the Dimension of ESG

On the basis of the ESG concept, in order to improve the level of sustainable and high-quality development, on the one hand, coal enterprises should focus on pollution and energy consumption reduction, employee safety and health protection and other aspects of the work, and reduce or even eliminate the occurrence of negative events. On the other hand, coal companies should enhance their green technology innovation level to help achieve the carbon neutrality target. In addition, coal enterprises should improve the transparency of social responsibility information, implement systematic construction, and increase investment in technological innovation, environmental protection, and intelligent construction [60].

6.3. Limitations and Future Work

In this study, we point out the direction for coal enterprises to improve the level of sustainable development. However, due to the limitation of some data sources and data volume, this study has many deficiencies that still need to be further supplemented and improved.

(1) In the research on theoretical mechanism, the index system needs to be further optimized. At present, environmental and social information disclosure of listed coal companies in China is not standardized and detailed. Considering the availability of data, we deleted the indexes that could not obtain data when constructing the performance evaluation index system. Future studies should actively promote the formulation of normative documents and guidelines for disclosing CSR reports in the coal industry. When the data are available, the deleted indicators should be re-incorporated into the index system, so that the overall performance of coal enterprises can be evaluated more comprehensively.

(2) In the research on model methods, the performance evaluation model needs to be further improved. The entropy method and cloud model are often used in data mining, risk evaluation, project evaluation, financial performance evaluation, and other fields. This is the first time that the cloud model has been applied to the performance evaluation of coal enterprises, and there are still many imperfections. In future studies, the model needs to be further improved and verified.

(3) In the case analysis, case samples need further horizontal comparative analysis. There is no uniform regulation on the disclosure of environmental performance and social performance data of coal enterprises in China, resulting in different information disclosure of different coal enterprises. Therefore, it is impossible to conduct a horizontal comparative analysis of the performance of the case company within the industry. In the future, when more data of coal enterprises can be obtained, the ESG-GT-EM-CM model framework constructed in this study might be used to conduct a horizontal comparative analysis on the performance of various coal enterprises in the industry.

(4) The coal enterprise performance evaluation index system constructed on the basis of grounded theory and ESG (ESG-GT) can be applied to other performance evaluation models in future research, in addition to the entropy method and cloud model. Furthermore, in the future, on the basis of the ESG-GT-EM-CM model framework, the performance level of each listed coal enterprise will be measured to fully verify the model framework. The financial performance, environmental performance, social performance, and governance performance of each coal enterprise are correspondingly measured, and the sustainable development performance of coal enterprise is comprehensively measured.

(5) In the era of big data, in future research, we plan to use data mining algorithms and models (such as neural networks, decision trees, and support vector machines) to build a performance evaluation index system and establish a performance evaluation model. Moreover, multi-case enterprise verification is carried out to achieve dynamic performance evaluation. Among them, the index system and model parameters should be able to realize timely adjustment. Then, enterprises can be enabled to find the right point of force and improve the performance level.

(6) With the popularization of the application scope of big data and artificial intelligence, future research should be based on models and algorithms such as machine learning, deep learning, and data mining to carry out data collection, data storage, data mining, and data analysis of big data in coal enterprises. On this basis, theoretical research and practical work on performance evaluation of coal enterprises are carried out, enabling intelligent governance and intelligent supervision of coal enterprises.