Does Managerial Myopia Affect Corporate Carbon Information Disclosure? Evidence from China

Abstract

Corporate carbon information disclosure (CID) is gradually transitioning from being voluntary to mandatory, consistent with the global consensus on addressing climate change and achieving sustainable development. CID reflects corporate environmental performance and is a crucial source for the market to comprehend corporate environmental risks and assess their long-term value. However, corporate operations are often influenced by managers’ behavioral preferences when formulating disclosure strategies, as managerial cognitive vision and values directly affect strategic decisions. This study used a sample of Chinese A-share-listed companies for 2010 to 2023 to investigate the relationship between managerial myopia and CID. The findings indicate that managerial myopia significantly inhibits CID by reducing executive environmental awareness and corporate green innovation capabilities. A heterogeneity analysis shows that managerial myopia has a stronger inhibitory effect on CID in companies with weak governance structures and those that are not technology-intensive, providing valuable references for environmental performance and CID practice in emerging countries.

1. Introduction

Corporate carbon information disclosure (CID) has become an important part of complying with environmental regulations, enhancing transparency, and fulfilling environmental responsibilities [1]. Although companies face continuous pressure regarding carbon disclosure practices from external stakeholders such as governments, investors, and consumers [2], in actual strategic decision-making they prefer to formulate disclosure strategies based on the trade-off between the costs and potential benefits of carbon disclosure [3]. CID may lead to higher information generation costs, disclosure compliance costs, and potential reputational risks [4]. However, it can also create benefits, such as an improved company image, enhanced investor trust, and increased market competitiveness [5].

In 2023, more than 30% of the world’s total carbon emissions came from China, one of the world’s largest carbon emitters [6]. Furthermore, China has the highest GDP-based emissions intensity among major economies, largely because industry accounts for about 39% of its GDP, which is above the global average of roughly 30% [7]. Thus, China faces great pressure to reduce carbon emissions. The Chinese economy has now moved from the stage of high-speed growth to high-quality development [8]. The 20th CPC National Congress states that the primary goal of high-quality development is to build an all-round modern socialist country [9]. The proposed goals of “carbon peaking” by 2030 and “carbon neutrality” by 2060 will have an impact on the environmental practices of Chinese listed companies [10]. In this context, the Chinese government is committed to taking stringent measures to reduce carbon emissions. For example, the implementation of carbon emission quota trading and the establishment of a unified carbon quota trading market nationwide have become important institutional innovations in the application of market mechanisms to control greenhouse gas emissions and promote green economic development in recent years. Therefore, studying the CID behavior of Chinese companies not only provides micro-level evidence for Chinese regulators to improve disclosure policies but also offers valuable insights for global investors to assess the transition risks of Chinese companies.

Management’s judgment and behavioral preferences play a vital role when deciding whether to disclose corporate carbon information. Upper echelons theory posits that corporate strategic decisions are largely influenced by managerial characteristics, such as a manager’s cognitive foundation, values and experience [11]. In recent times, researchers have focused on how the personal characteristics of chief executive officers (CEOs) and senior management teams (i.e., gender, age, educational background, and professional experience) can affect corporate environmental information disclosure behaviors [12,13]. However, most of the current studies concentrate on differences in personal characteristics and pay less attention to how managers think and make decisions, especially the effect of their psychological tendencies in the trade-off between short- and long-term interests on carbon disclosure strategies.

Managerial myopia, a behavioral tendency wherein managers focus on short-term performance and ignore long-term strategic value, has attracted widespread research attention in recent times. Existing studies have shown that managers with short-term views are more likely to cut research and development (R&D) investment and ignore corporate social responsibility in exchange for short-term financial results [14]. This tendency may cause management to adopt inactive strategies when facing risks and reduce disclosure to avoid short-term risks [15], which affects the way their companies implement sustainable development strategies. Therefore, this study explores the impact of managerial myopia on corporate CID decisions as an attempt to close the research gap in current research and provide theoretical support and empirical evidence for optimizing corporate environmental governance and information disclosure. In addition, this paper considers the following questions: (1) Through what mechanisms does managerial myopia affect corporate CID? (2) Is the impact of managerial myopia on corporate CID heterogeneous?

This study makes several contributions to existing literature. First, previous research has not reached a consensus on how CID can be measured. Existing studies primarily measure CID through methods such as the Committee for Development Policy (CDP) questionnaire [16], the construction of a carbon disclosure index [17], and the extraction of keywords [18]. This study uses a new CID measure by adopting the established carbon disclosure index of companies listed on the China Stock Market and Accounting Research (CSMAR) database. Compared with the aforementioned methods, this index’s measurement is more comprehensive, as it refers to the Corporate Sustainability Disclosure Standards: Basic Guidelines and International Financial Reporting Standards (IFRS) on climate-related disclosures. The index is further subdivided into four dimensions, governance, strategy, risk and opportunity management, as well as indicators and targets. In addition, the data for this index, which are extracted from corporate annual reports, social responsibility reports, and sustainable development reports, are more reliable and comparable; moreover, a standardized scoring system is applied to ensure data consistency and comparability. Second, we extend the research on the factors that influence CID from the perspective of long-term management goals. Corporate management typically takes a trade-off between short- and long-term goals when making CID decisions, and business strategic choices are influenced by managerial strategic vision. This study uses the perspective of managerial myopia to offer empirical evidence on the effect of management strategic goals on CID in Chinese companies, which should have significant practical implications. Various stakeholders can benefit from a better understanding of the role of CID in corporate governance with respect to managerial views and decision-making in terms of the impact of management myopia—not only in China but also for emerging markets. Furthermore, policymakers should consider introducing more mandatory, comprehensive, and auditable carbon disclosure standards, requiring companies to disclose not only qualitative targets but also quantitative, comparable carbon emissions and reduction data, which will help reduce the likelihood of selective concealment by management. Regulators could incorporate the quality of carbon disclosure into corporate governance evaluation systems and encourage boards of directors to establish dedicated committees to oversee climate change-related risks, thereby mitigating the negative impact of managerial myopia.

2. Literature Review and Hypothesis Development

2.1. Literature Review

Managerial myopia refers to corporate management behavior that focuses on short-term interests and loses sight of long-term development when making business decisions [19]. Previous studies have examined the factors that contribute to management myopia in-depth. Some researchers report that elements such as capital market pressure [20], managerial compensation [21], and personal managerial characteristics [22] can lead to managerial myopia. From an economic perspective, managerial myopia dampens corporate strategies and long-term value. On the one hand, shortsighted managerial behavior significantly reduces corporate investment in R&D, innovation, and human capital [15], weakening a firm’s core competitiveness. On the other hand, shortsighted management is more inclined to engage in earnings management and accounting manipulation, reducing firms’ financial transparency [23]. Additionally, managerial myopia inhibits corporate green innovation [15] and reduces the quality of environmental disclosures [24], undermining corporate social responsibility and long-term sustainable strategies [25]. Although the above studies provide strong evidence for understanding the consequences of shortsighted corporate behavior, the motivation and practice of CID is still an under-researched area.

CID is an important tool for addressing climate change risk and demonstrating corporate environmental responsibilities. From the determinant perspective, institutional pressure and stakeholder expectations are the two core factors that motivate companies to disclose carbon information. Institutional theory emphasizes that external institutional pressures, such as government regulation and international disclosure initiatives (e.g., CDP), are important drivers of corporate disclosure [26]. Stakeholder theory suggests that demand for environmental information from investors, customers, and non-governmental organizations has prompted companies to increase carbon transparency [27]. At the corporate governance level, the proportion of independent directors, the participation of female directors, and the level of foreign shareholdings have also been found to be positively correlated with corporate disclosure behavior [28]. In addition, large companies or companies with strong profitability are more capable of coping with disclosure costs and risks and, compared with other companies, often demonstrate higher enthusiasm for disclosure [29]. In terms of economic consequences, although existing literature confirms that high-quality disclosure can enhance corporate reputation [30] and reduce financing costs [31], it rarely explores how managerial myopia affects CID. In theory, managers with managerial myopia are more likely to avoid disclosure activities that have high short-term costs and delayed returns, such as carbon emissions measurement and external audits [32]. This behavior not only weakens the authenticity of corporate environmental governance but may also hinder the capital market’s correct assessment of the company’s long-term value. Therefore, directly linking managerial myopia with corporate CID not only fills the gap in research on the economic consequences of managerial myopia but also responds to the new requirements for corporate environmental transparency under global climate governance and carbon neutrality strategies.

2.2. Hypothesis Development

2.2.1. Managerial Myopia and CID

Consistent with the global consensus on addressing climate change and achieving sustainable development, corporate CID is gradually evolving from voluntary to mandatory disclosure [33]. CID reflects corporate environmental responsibility and is a crucial channel for the market to comprehend corporate environmental risks and judge their long-term value [34]. However, CID usually involves complex measurement and disclosure processes that may trigger regulatory accountability or market suspicions, and management behavioral preferences play a key role in formulating relevant corporate disclosure strategies [35]. Therefore, managerial myopia, a typical managerial preference, may significantly impact corporate CID decisions and practice.

Managers who lack foresight tend to prioritize immediate financial results to meet market expectations of current-period profitability [36]. This short-term orientation often leads managers to have a negative attitude toward environmental information disclosure, which requires a long input–output cycle with uncertain financial returns [37]. Although CID can enhance corporate reputations and market trust in the long run, its initial investment costs, difficulty in data collection, and potentially negative exposure risks often cause the shortsighted management to ignore CID [38].

Additionally, management shortsightedness weakens the emphasis on environmental sustainability, reducing managerial environmental cognition. A high level of environmental responsibility cognition indicates that management is aware of environmental risks and how they impact a company’s long-term growth. Therefore, management is more willing to disclose information related to carbon emissions to demonstrate its environmental commitment [39]. However, shortsighted management often focuses on quarterly earnings and stock price fluctuations and loses sight of matters such as environmental protection investment and information disclosure, which makes it difficult to achieve quick financial returns [32]. Therefore, management shortsightedness reduces the level of corporate environmental awareness, resulting in a lack of cognition for disclosing proper and sufficient carbon information.

Finally, managerial myopia may reduce corporate investments in environmentally friendly innovation, reducing the extent and quality of CID. Green innovation requires continuous capital investment and technological acquisition [40]. Shortsighted management with prioritization of short-term interests may incline to cut expenditures that have only long-term benefits, such as R&D and environmental protection investments, to maximize the company’s short-term financial performance [36]. The lack of green innovation constrains environmental performance results that companies can disclose and weakens managerial motivation to show a positive corporate environmental image and social responsibility, thus inhibiting active CID in practice [41]. Based on this discussion, the following hypothesis is proposed for empirical investigation:

H1. 

Managerial myopia restrains corporate CID.

2.2.2. The Mechanism of Executives’ Green Awareness

Green cognition reflects executives’ awareness of and attitudes toward environmental issues and is a key psychological basis for promoting environmental management practices and information disclosure [42]. Business executives with higher levels of environmental awareness are more likely to recognize the value of environmental responsibility for a company’s long-term growth and actively promote sufficient and transparent CID [43]. However, green cognition is often ignored when the management focuses excessively on short-term performance. Management shortsightedness inhibits executives’ attention to environmental strategies and weakens the weight placed on a corporate environmental agenda [16]. This cognitive deficiency dampens the initiatives related to the collection, analysis, and disclosure of carbon emission data. Additionally, cognitive psychology research has found that management’s behavioral biases negatively affect information processing and analysis capabilities [44]. Shortsighted thinking patterns make management more inclined to choose low-risk and fewer investment business strategies to avoid issues with high short-term return uncertainty in the environmental field [37]. Drawing on the above analysis, we further point out that managerial myopia dampens corporate green cognition of the strategic significance of CID, leading to a decrease in the extent of CID.

H2. 

Managerial myopia inhibits corporate CID by reducing executives’ green awareness.

2.2.3. The Mechanism of Green Innovation

Green innovation is a comprehensive business capability for making environmentally friendly improvements in product design, production processes, energy usage, and management systems [40]. It reflects the strength of a company’s execution of its environmental strategy, directly affecting the content and quality of CID. Companies with green innovation capabilities often have more systematic and quantifiable carbon emissions data than those without these capabilities; they are more willing to display their environmental governance results to lift their social responsibility image and obtain policy support and market trust [45]. However, shortsighted management behavior significantly curbs the progress of green innovation. Since green innovation requires long-term capital investment, technology accumulation, and cross-departmental coordination, it is often treated as a “cost center” rather than as a “value creator” by the shortsighted management [46]. The consequences of green innovation take a long time to appear, which conflicts with the performance evaluation orientation of the shortsighted business executives [15]. Therefore, companies with shortsighted managers often cut their green R&D spending, ultimately constraining their ability and willingness to disclose carbon information. In summary, the following hypothesis is proposed:

H3. 

Managerial myopia inhibits corporate CID by hindering corporate green innovation.

Figure 1 presents the logic of the research structure for this study.

3. Study Design

3.1. Sample Selection

The sample consists of Chinese A-share businesses listed on the Shanghai and Shenzhen Stock Exchanges from 2010 to 2023. Green patent data are collected from the Chinese Research Data Services Platform (CNRDS); other financial data used in this study are extracted from the CSMAR database, the most popular database for research on the Chinese capital market. Companies in the financial sector, those with ST and ST* status, or those missing data are excluded. All continuous variables were winsorized at the 1% and 99% levels to eliminate the impact of outliers. The final sample comprises 28,558 firm-year observations.

3.2. Definition of Variables

3.2.1. Independent Variable

Currently, there is a lack of uniform measurement criteria for the format and content of CID. The content analysis method is typically scored by individual researchers, which may be highly subjective. Although a few international organizations, such as the CDP and Global Reporting Initiative, have attempted to set certain carbon emission reporting initiatives, the content of CID is yet to be standardized, and significant differences exist in the disclosures by companies [47]. This lack of uniformity makes it difficult for stakeholders to evaluate and compare the carbon emissions information of various companies [48]. In this study, environmental performance disclosures compiled by a third party (CSMAR) are used to measure corporate CID. We believe that using the CSMAR database has specific advantages. First, the database is widely used for studies of listed Chinese companies [49]. Its corporate environmental data are derived from the annual, social responsibility, and sustainable development reports of listed companies, which can ensure data reliability [50]. Additionally, data collection and scoring procedures are conducted consistently through the CSMAR database, and its standardized scoring system can effectively compare the CID performance of different companies, ensuring the objectivity and consistency of the related data.

Thus, we use the carbon information disclosure index for the sample of Chinese companies extracted from the CSMAR database. This database constructed the carbon disclosure index based on the four-element disclosure framework of governance, strategy, risk, and opportunity management as shown in the recommendations report of the Task Force on Climate-related Financial Disclosures formed by the Financial Stability Board, the indicators and targets proposed in the Corporate Sustainability Disclosure Standards: Basic Guidelines (2024), and guidelines in IFRS S2 Climate-Related Disclosures. Each disclosure element of the index is subdivided, with its content scored qualitatively or quantitatively. Finally, we obtain corporate CID scores in the range of (0, 50). The measurement instruments are presented in

Table 1. Construction of the Carbon Disclosure Assessment Scale.

Variables	Environmental Category	Measurement	Maximum Score
Governance	Board supervision	1 = Disclosure of environmental philosophy, environmental policies, environmental management organizational structure, circular economy development model, green development, etc., 0 = None.	1
	Management responsibilities	1 = Information disclosed on managerial-level institutions responsible for climate change management, 0 = None.	1
	Employee participation	1 = Disclosure of the company’s mechanism for promoting employee participation in carbon emission reduction, including environmental protection-related education and training, 0 = None, 2 = Maximum score.	2
Risk management	Risk management system	1 = Disclosure of the company’s environmental management system, policy, regulations, responsibilities, and other management system information related to identifying, assessing, and responding to climate-related risks and opportunities, 0 = None.	1
	Risk identification and assessment	1 = Disclosure of climate-related risks that affect the company’s financial or business development, 0 = None.	1
Opportunity management	Opportunity identification and assessment	1 = Disclosure of climate-related opportunities that may affect the company’s finances or business development, 0 = None.	1
Strategy	Low-carbon transformation strategy	1 = Disclosure of low-carbon transformation strategy, 0 = None.	1
Indicators	Scope 1 greenhouse gas emissions 1	4 = Quantitative description, 2 = Qualitative description, 0 = None.	4
	Scope 2 greenhouse gas emissions 2	4 = Quantitative description, 2 = Qualitative description, 0 = None.	4
	Scope 3 greenhouse gas emissions 3	4 = Quantitative description, 2 = Qualitative description, 0 = None.	4
	Carbon emission intensity	4 = Quantitative description, 2 = Qualitative description, 0 = None.	4
	Emissions changes	4 = Quantitative description (Scope 1 and Scope 2), 2 = Qualitative description, 0 = None.	4
	Scope 1 emission breakdown	2 = Disclosure of Scope 1 emissions breakdown by greenhouse gas type, country/region, or subsidiary/business/department, 0 = None.	2
	Scope 2 emission breakdown	2 = Disclosure of Scope 2 emissions breakdown by greenhouse gas type, country/region, or subsidiary/business/department, 0 = None.	2
	Value chain engagement	1 = Disclosure of climate-related interactions with value chain entities, including collecting customer/supplier climate data or encouraging participation in climate actions, 0 = None.	1
	Upstream and downstream customer management	1 = Disclosure of managing climate risk activities in the supply chain, such as whether meeting climate requirements is part of the procurement process, 0 = None.	1
	Other climate information	1 = Disclosure of other climate-related indicators relevant to business operations, 0 = None.	1
	Verifiability	1 = Disclosure of carbon emission data with ISO 14001 environmental management system certification or other third-party assurance, 0 = None.	1
Targets	Carbon reduction targets	4 = Quantitative description, 2 = Qualitative description, 0 = None.	4
	Other climate management targets	2 = Disclosure of any other climate-related targets, 0 = None.	2
	Emission reduction measures	4 = Quantitative description, 2 = Qualitative description, 0 = None.	4
	Business transformation progress	4 = Quantitative description, 2 = Qualitative description, 0 = None.	4
Total			50

¹ Scope 1 greenhouse gas emissions are direct emissions from resources owned and controlled by the company; ² Scope 2 greenhouse gas emissions are indirect emissions from purchased energy, including electricity, steam, heating, and cooling; ³ Scope 3 greenhouse gas emissions are all indirect emissions occurring within the reporting company’s value chain (not included in Scope 2); “Quantitative description” refers to companies reporting the actual results of emissions with specific numbers, which answers the question of how much is emitted and focuses on performance and results. “Qualitative description,” in contrast, refers to a company’s non-digital display of how it manages and responds to emissions through text descriptions, policy statements, management frameworks, and similar disclosures. It answers the question of how the company does it and focuses on management processes and strategies.

.

3.2.2. Dependent Variable

The core characteristic of managerial myopia is an excessive focus on short-term gains at the expense of long-term value [51]. Some studies use questionnaires to measure managerial myopia [52], which may have problems such as limited sample size and subjectivity. Other scholars use R&D expenditure to measure managerial myopia [53], which may not directly reflect the actual cognition of managers. In addition, some scholars use text analysis to conduct research. Given that personal traits and behavioral preferences are reflected in written documents, we believe that examining lexical categories and frequencies in an experimental subject statement can better capture management characteristics [54]. This method can accurately and deeply portray the short-sighted behavior of managers while avoiding measurement errors and subjective bias. Management discussion and analysis (MD&A) is a written report by corporate management, summarizing the company’s operating results during the reporting period and explaining the next phase of business strategies, potential opportunities, and related risks. Previous research has shown that the personal characteristics of senior executives significantly influence the content and style of corporate disclosures [55]. Therefore, the frequency of words related to short-term pressures, goals, and performance in MD&A can directly reflect management’s focus and cognitive framework during a specific period. Following Hu et al. [56], we employ text analysis to assess managerial myopia. Management’s report is reflected in the MD&A section of a company’s annual report [57]; investors can forecast stock price movements [58] and corporate success [59] by using the disclosed information.

Therefore, we measure managerial myopia by using the relative frequency of shortsightedness-related words in the MD&A portion of corporate annual reports. Following the text index methodology proposed by Li [60], the English lexicon of shortsighted behavior proposed by Brochet et al. [21], and the linguistic features in the 500 Chinese-language MD&A documents used by Hu et al. [56], we finally identified 43 Chinese and English words or linguistic phrases that can indicate managerial myopia, such as “as soon as possible,” “immediately,” and “opportunity.” Subsequently, we calculated the ratio of the frequencies of these myopic behavior words to the total number of words in the MD&A section and multiplied it by 100 to measure managerial myopia (Myopia). Higher Myopia values indicate higher levels of managerial shortsightedness.

3.2.3. Mechanism Variables

Green innovation (GP): We used green patents to proxy for green innovation. The data are derived from the green patent research database established by the CNRDS, which provides information on green patents of listed Chinese companies. First, a company’s patent applications reflect its innovation activities [61]. Second, contrary to the number of patent approvals, the number of patent applications can more accurately represent the actual efforts of innovation [62]. Finally, patent application count is commonly employed in prior research to indicate a firm’s innovative capability [63]. Following Hao et al. [64], we use the natural logarithm of green patent applications plus 1 to measure a company’s green innovation performance.

Executive environmental awareness (EGP): Following Liu and Cao [43], this study uses content analysis to evaluate the annual reports of listed companies and divides executives’ environmental awareness into three dimensions: green competitive advantage awareness, corporate social responsibility awareness, and external environmental pressure awareness. A series of keywords are selected for the above dimensions. Executive environmental awareness is quantified as the frequency with which these terms appear in corporate annual reports and serves as a measure of green attention in managerial decision-making in the sample companies.

3.2.4. Control Variables

The control variables are selected in line with previous studies [46,65]. This study controls for return on assets (Roa), the asset–liability ratio (Lev), operating revenue growth rate (Growth), board size (Board), duality of board chairman and CEO positions (Dual), shareholding concentration (Top1), management shareholdings (Mhold), institutional shareholdings (Ins), and company size (Size). Furthermore, the fixed impacts related to year and industry are accounted for to eliminate unobservable yearly and industrial disparities. A variance inflation factor (VIF) test is performed on these variables, with an average VIF value of 1.59, suggesting that no overt multicollinearity problems exist. The definitions of all variables are presented in

Table 2. Variable definitions.

Variables	Definition	Symbol	Measurement
Dependent variable	Carbon information disclosure	CID	Score derived from the index construction as presented in Table 1.
Independent variables	Managerial myopia	Myopia	Total myopic behavior words × 100/total MD&A words.
Intermediate variable	Green innovation	GP	The natural logarithm of government subsidies plus 1 at the end of the year.
	Executive environmental awareness	EGP	Calculated by weighting the importance of green competitive advantage, corporate social responsibility, and external environmental pressure.
Control variables	Firm size	Size	The natural logarithm of the firm’s total assets at the end of the year.
	Return on assets	Roa	Net profit/total assets at the end of the year.
	Leverage	Lev	Total liabilities/Total assets.
	Growth rate	Grow	(Operating income at the end of the current year − operating income at the end of the previous year)/(Operating income at the end of the previous year).
	Board size	Board	The natural logarithm of the number of directors on the board.
	CEO duality	Dual	The same person holds both the chairperson and general manager positions, 1; otherwise, 0.
	Ownership concentration	Top1	The shareholding ratio of the company’s largest shareholder.
	Mhold	Mhold	Number of shares held by managers/total shares at the end of the year.
	Ins	Ins	Number of institutional holding shares/total number of shares.

.

3.3. Empirical Models

To examine how managerial myopia impacts CID, we constructed the baseline regression model shown in Equation (1):

$${CID}_{i,t}={\alpha }_0+{\alpha }_1{Myopia}_{i,t}+{\alpha }_2{Controls}_{i,t}+\sum Year+\sum Industry+{\epsilon }_{i,t}$$

(1)

${CID}_{i,t}$ proxies for the CID of enterprise i in year t. ${Myopia}_{i,t}$ is the level of managerial myopia of enterprise i in year t. $Controls$ represents the control variables. The model also includes controls for year and industry fixed effects. Additionally, the estimated standard errors are clustered at the company level.

To examine how executive environmental awareness and green innovation mediate the association between managerial myopia and CID, we construct the analytical models in Equations (2)–(5):

$${GP}_{i,t}={\alpha }_0+{\alpha }_1{Myopia}_{i,t}+{\alpha }_2{Controls}_{i,t}+\sum Year+\sum Industry+{\epsilon }_{i,t}$$

(2)

$${CID}_{i,t}={\beta }_0+{\beta }_1{Myopia}_{i,t}+{\beta }_2{GP}_{i,t}+{\beta }_3{Controls}_{i,t}+\sum Year+\sum Industry+{\epsilon }_{i,t}$$

(3)

$${EGP}_{i,t}={\alpha }_0+{\alpha }_1{Myopia}_{i,t}+{\alpha }_2{Controls}_{i,t}+\sum Year+\sum Industry+{\epsilon }_{i,t}$$

(4)

$${CID}_{i,t}={\beta }_0+{\beta }_1{Myopia}_{i,t}+{\beta }_2{EGP}_{i,t}+{\beta }_3{Controls}_{i,t}+\sum Year+\sum Industry+{\epsilon }_{i,t}$$

(5)

4. Empirical Results

4.1. Descriptive Statistics

Table 3. Descriptive statistical analysis.

Variables	N	Mean	Std	Min	Max
CID	28,558	11.659	9.151	0.000	41.000
Myopia	28,558	0.037	0.030	0.000	0.162
Roa	28,558	0.041	0.059	−0.303	0.198
Lev	28,558	0.398	0.194	0.051	0.948
Growth	28,558	0.159	0.363	−0.608	2.680
Board	28,558	2.115	0.194	1.609	2.639
Dual	28,558	0.312	0.463	0.000	1.000
Top1	28,558	33.992	14.495	8.440	74.020
Mhold	28,558	0.161	0.204	0.000	0.690
Ins	28,558	41.962	25.273	0.367	90.906
Size	28,558	22.217	1.239	19.699	26.150

presents the descriptive statistics of the primary variables of this study. The dataset includes 28,558 firm-year observations from 2010 to 2023. The mean of CID is 11.659, with a minimum and maximum of 0 and 41, respectively, suggesting that the sample of listed companies has a wide variation in CID. Myopia has an average value of 0.037, with a standard deviation of 0.030 and ranging from a minimum of 0 to a maximum of 0.162. These findings indicate that common management myopia exists in publicly traded corporations, with sufficient variation in indicators of management myopia. The results of the remaining control variables are generally consistent with those reported in previous studies.

4.2. Baseline Specification

Table 4. Results of baseline regression.

	(1)	(2)
Variables	CID	CID
Myopia	−6.563 ***	−4.166 ***
	(−4.222)	(−2.741)
Size		2.594 ***
		(14.533)
Roa		3.258 ***
		(3.488)
Lev		−1.873 ***
		(−3.258)
Growth		−0.525 ***
		(−5.108)
Board		−0.472
		(−1.013)
Dual		0.042
		(0.257)
Top1		0.019 *
		(1.735)
Mhold		4.537 ***
		(7.090)
Ins		0.034 ***
		(5.849)
Constant	5.409 ***	−51.322 ***
	(28.538)	(−13.390)
N	28,558	28,558
Year	Yes	Yes
Industry	Yes	Yes
Adjusted R2	0.444	0.468

* and *** denote significance at the 10% and 1% levels, respectively.

presents the effect of managerial myopia on a company’s CID, estimated using Equation (1). The results in both columns incorporate year and industry fixed effects. The regression in Column (1) includes only Myopia and CID, without incorporating control variables. Column (2) shows the relationship between Myopia and CID, including the control variables. The results show that a 1-unit increase in managerial myopia leads to an average decrease of approximately 4.166 units in corporate carbon disclosure, and this negative relationship is significant at the 1% level, indicating that companies with higher managerial myopia have lower levels of CID, supporting H1. The coefficients of the control variables generally align with those found in prior research. Companies with higher profitability, lower financial leverage, higher management ownership, and institutional investor shareholdings, and that are larger in scale tend to disclose more carbon information than their peers.

4.3. Robustness Tests

4.3.1. Alternative Measurement of Management Myopia

This study further selects quantitative indicators to remeasure managerial myopia to better evaluate the validity of the independent variable measurements. Following Gao et al. [66], we directly assess managerial myopia by scaling short-term investments in the current period to the total assets at the beginning of the period. For investments before 2007, we use the “net short-term investments” account, and the sum of the accounts of “trading financial assets,” “net value of available-for-sale financial assets,” and “net value of held-to-maturity investments” is used to measure managerial myopia for investments after 2007 (China implemented new accounting standards in 2007. The new standards abolished the original concept of “net short-term investments” and replaced it with the sum of “trading financial assets,” “net value of available-for-sale financial assets,” and “net value of held-to-maturity investments.”). Column (1) of

Table 5. Results of robustness tests (variable replacement and lagged variable).

	(1)	(2)	(3)
Variables	CID	CID	CID
Myopia2	−2.980 ***
	(−3.870)
L1Myopia		−4.282 **
		(−2.526)
L2Myopia			−4.125 **
			(−2.276)
Size	2.622 ***	2.722 ***	2.932 ***
	(14.675)	(13.431)	(13.203)
Roa	3.386 ***	3.148 ***	2.068 **
	(3.635)	(3.185)	(2.015)
Lev	−2.034 ***	−2.053 ***	−1.996 ***
	(−3.530)	(−3.128)	(−2.729)
Growth	−0.486 ***	−0.459 ***	−0.428 ***
	(−4.775)	(−3.949)	(−3.389)
Board	−0.461	−0.146	−0.023
	(−0.990)	(−0.285)	(−0.040)
Dual	0.048	−0.012	−0.037
	(0.293)	(−0.065)	(−0.191)
Top1	0.020 *	0.021 *	0.023 *
	(1.782)	(1.653)	(1.761)
Mhold	4.469 ***	4.667 ***	5.051 ***
	(6.971)	(6.322)	(6.213)
Ins	0.034 ***	0.037 ***	0.043 ***
	(5.800)	(5.662)	(5.844)
Constant	−52.010 ***	−54.916 ***	−59.353 ***
	(−13.570)	(−12.553)	(−12.375)
N	28,558	23,181	19,693
Year	Yes	Yes	Yes
Industry	Yes	Yes	Yes
Adjusted R2	0.468	0.458	0.457

*, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively.

shows the regression results after the replacement. These findings support H1 by demonstrating that the effect of managerial myopia on CID is negative and significant at the 1% level. This indicates that the main results are reliable when the measurement of the explanatory variable is changed.

4.3.2. Lagged Independent Variable

Since the effect of managerial myopia on corporate CID may not be immediately apparent, this study considers the lag effects to mitigate potential endogeneity issues. Following Xie et al. [67], the independent variable is lagged by one (L1Myopia) and two (L2Myopia) periods. In Table 5, the coefficients of Myopia in Columns (2) and (3) are both noticeably negative, indicating that managerial myopia has a long-lasting impact on CID. Furthermore, the regression results are aligned with those of the benchmark regression, which enhances the reliability of our main study findings.

4.3.3. Additional Fixed Effects

Following Lu et al. [65], we consider that different industries may be impacted by cyclical operations and policy considerations throughout the study period. Therefore, the year–industry interaction fixed effects based on Model (1) is further controlled in this analysis, and the results are shown in Column (1) of

Table 6. Results of robustness tests (additional fixed effect and industry exclusion).

Variables	(1)	(2)
	CID	CID
Myopia	−3.756 **	−4.854 ***
	(−2.413)	(−2.615)
Size	2.583 ***	2.724 ***
	(14.691)	(12.472)
Roa	1.923 **	2.992 ***
	(2.045)	(2.854)
Lev	−1.940 ***	−1.398 **
	(−3.371)	(−1.983)
Growth	−0.521 ***	−0.603 ***
	(−4.923)	(−5.087)
Board	−0.295	−0.324
	(−0.653)	(−0.596)
Dual	0.114	0.041
	(0.715)	(0.215)
Top1	0.022 **	0.030 **
	(2.008)	(2.348)
Mhold	4.083 ***	4.612 ***
	(6.351)	(6.222)
Ins	0.027 ***	0.033 ***
	(4.907)	(4.881)
Constant	−51.036 ***	−55.197 ***
	(−13.371)	(−11.882)
N	28,558	20,539
Year	Yes	Yes
Industry	Yes	Yes
Year × Industry	Yes	No
Adjusted R2	0.483	0.457

**, and *** denote significance at the 5%, and 1% levels, respectively.

. The coefficient of managerial myopia is −3.756, which is significantly negative at the 10% level. The results indicate that even after controlling for the possible influence of factors at the macro level, the coefficient of managerial myopia remains significantly negative, which is in line with the baseline regression findings of this study.

4.3.4. Eliminate Heavily Polluting Industries

Following the Administrative Measures for the Legal Disclosure of Enterprise Environmental Information issued by the central government, companies in highly polluting sectors must disclose information about pollutants and carbon emissions [68]. To mitigate the concern that companies in highly polluting industries are mandated to release environmental information, sample companies in 16 heavily polluting industries are excluded by referring to the industrial classification set by the Ministry of Environmental Protection of China in 2010 and the China Securities Regulatory Commission in 2012. Column (2) of Table 6 presents the results of the regression after excluding these observations. The coefficient of Myopia is −4.854 and is significant at the 1% level, confirming the validity of the main findings.

4.3.5. Propensity Score Matching

Self-selection bias is another factor to be addressed when evaluating the negative effect of management myopia on corporate CID. Referring to Atif and Ali [69], we employ the PSM method to mitigate the endogeneity issue of sample self-selection. Following Xie et al. [67], we classify companies with shortsighted management behavior higher than the median of the sample as the experimental group, and those with shortsighted management behavior below the median as the control group for the PSM test; all control variables are included as covariates. The 1:1 nearest neighbor matching method is used to match each observation in the experimental group with a similar company in the control group, while companies not successfully matched are eliminated. We run the regression again by using the matched samples, and the results are displayed in Column (1) of

Table 7. Results of robustness tests (PSM and instrument variable).

	(1)	(2)	(3)
Variables	CID	Myopia	CID
Myopia	−3.542 *		−52.032 ***
	(−1.762)		(−17.008)
IV	4.346 ***	0.948 ***
	(3.235)	(101.686)
Size	−46.852 ***	−0.001 *	5.772 ***
	(−9.739)	(−1.957)	(37.456)
Roa	−2.117 ***	−0.008 ***	−4.466 ***
	(−2.798)	(−2.614)	(−4.052)
Lev	−0.492 ***	0.004 **	−1.696 **
	(−3.280)	(2.257)	(−2.482)
Growth	−0.468	−0.002 ***	−1.449 ***
	(−0.770)	(−4.605)	(−11.784)
Board	−0.069	−0.001	−2.533 ***
	(−0.339)	(−0.574)	(−4.455)
Dual	0.022	−0.001 **	−0.101
	(1.601)	(−2.517)	(−0.523)
Top1	3.357 ***	−0.000	−0.038 ***
	(4.013)	(−0.070)	(−2.915)
Mhold	0.035 ***	−0.003	−2.856 ***
	(4.671)	(−1.513)	(−3.931)
Ins	2.398 ***	−0.000 **	−0.004
	(10.729)	(−2.297)	(−0.578)
Constant	−3.542 *
	(−1.762)
N	14,468	28,220	28,220
Year	Yes	Yes	Yes
Industry	Yes	Yes	Yes
Adjusted R2	0.471		0.141

*, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively.

. The coefficient of Myopia is −3.542 and is significant at the 10% level. This suggests that our main empirical conclusions are robust after controlling for self-selection bias.

4.3.6. Instrumental Variable Method

Referring to the literature, we employ an instrumental variable (IV) to mitigate the endogeneity problem that may be caused by reverse causality and omitted variable concerns. Following Mingqiang et al. [46], we use the average management myopia in the same year and region (IV_Myopia) as an instrumental variable, which is unlikely to be coincident with that of individual enterprises. First, IV_Myopia is regressed on Myopia. Next, the fitted values of the first-stage regression are used as the independent variable to rerun the baseline regression based on Equation (1). The regression results using the IV are displayed in Table 7. Column (2) shows that the coefficient of IV_Myopia is 0.948, which is significant at the 1% level. The results indicate a significant association between IV_Myopia and Myopia, satisfying the correlation requirement for an IV. Furthermore, the F-statistic is greater than 10, indicating that IV_Myopia is a valid instrumental variable. Column (3) shows that the coefficient of managerial myopia is notably negative and significant at the 1% level, supporting the baseline regression conclusion. Therefore, our findings are robust even after considering potential reverse causality.

4.3.7. Paris Agreement

The 2015 Paris Agreement established global temperature control targets and strengthened national emission reduction commitments, shifting the capital market’s pricing of carbon emissions risk. Carbon disclosure has gradually moved from a voluntary to a mandatory regime. Existing research shows that, since 2015, institutional investors and financial markets have begun to view carbon emissions as a significant financial and reputational risk, increasing the capital market value of corporate carbon disclosure [70]. This shift in perception has led investors to pay more attention to corporate carbon transparency and exert greater pressure on high-emitting companies to disclose carbon information. With the gradual improvement of policies, investor attention to carbon disclosure has increased significantly [71]. Executives who neglect carbon disclosure due to shortsightedness will be more susceptible to capital market influence.

Thus, we divide the sample into two time periods according to the signing of the Paris Agreement: before 2015 and after 2015. We conduct group regression by time interval (the regression results are shown in

Table 8. Results of pre- and post–Paris Agreement robustness tests.

Variables	(1)	(2)
	CID Before Paris Agreement	CID After Paris Agreement
Myopia	2.331	−6.435 ***
	(1.395)	(−3.076)
Size	1.097 ***	3.351 ***
	(4.637)	(13.302)
Roa	2.442	1.975 *
	(1.516)	(1.960)
Lev	−0.977	−2.331 ***
	(−1.313)	(−2.938)
Growth	−0.217	−0.645 ***
	(−1.546)	(−4.953)
Board	−0.504	−0.263
	(−0.871)	(−0.448)
Dual	−0.017	0.041
	(−0.078)	(0.207)
Top1	−0.007	0.023
	(−0.471)	(1.455)
Mhold	−0.270	4.756 ***
	(−0.301)	(5.157)
Ins	0.002	0.042 ***
	(0.370)	(4.952)
Constant	−15.956 ***	−67.698 ***
	(−3.124)	(−12.336)
N	7663	20,895
Year	Yes	Yes
Industry	Yes	Yes
Adjusted R2	0.054	0.454

*and *** denote significance at the 10% and 1% levels, respectively.

). After the signing of the Paris Agreement, the inhibitory effect of managerial shortsightedness on corporate carbon disclosure has become more pronounced. The signing of the Paris Agreement has had a significant impact on companies and management. Compared with reputational gains, short-term managers are more concerned with the short-term costs and potential risks (such as compliance costs or litigation risks) of carbon disclosure. This leads to a significantly lower willingness to disclose carbon information when management’s short-term vision increases.

5. Mechanism Analysis

5.1. Analysis of the Functional Mechanism

From the previous analyses, we posit that managerial myopia inhibits CID by reducing executives’ green cognition (i.e., green awareness) and green innovation. The tests conducted to validate these two mechanisms and their results are described in this section.

5.1.1. Executive Environmental Awareness

Managerial myopia may inhibit executives’ attention to environmental strategies, reduce their green cognition [15], and dampen corporate CID. Text analysis can effectively measure executive cognition and is widely used in empirical research [72]. Columns (1) and (2) of

Table 9. Results of mechanic functioning tests.

	(1)	(2)	(3)	(4)
Variables	EGP	CID	GP	CID
Myopia	−0.316 *	−3.736 **	−0.297 **	−4.065 ***
	(−1.742)	(−2.480)	(−2.141)	(−2.683)
EGP		1.360 ***
		(15.235)
GP				0.340 ***
				(3.836)
Size	0.069 ***	2.500 ***	0.078 ***	2.567 ***
	(3.660)	(14.258)	(4.513)	(14.388)
Roa	0.192 **	2.997 ***	0.157 *	3.205 ***
	(2.034)	(3.254)	(1.825)	(3.440)
Lev	−0.100	−1.737 ***	−0.038	−1.860 ***
	(−1.527)	(−3.079)	(−0.750)	(−3.240)
Growth	0.003	−0.529 ***	−0.031 ***	−0.515 ***
	(0.261)	(−5.275)	(−3.636)	(−5.005)
Board	−0.068	−0.379	−0.065	−0.450
	(−1.296)	(−0.825)	(−1.473)	(−0.969)
Dual	−0.002	0.044	−0.011	0.045
	(−0.113)	(0.278)	(−0.731)	(0.280)
Top1	−0.001	0.020 *	−0.001	0.019 *
	(−0.447)	(1.841)	(−0.718)	(1.763)
Mhold	0.132 *	4.358 ***	0.089	4.507 ***
	(1.746)	(7.021)	(1.481)	(7.058)
Ins	0.000	0.034 ***	−0.000	0.034 ***
	(0.034)	(5.962)	(−0.365)	(5.883)
Constant	−0.483	−50.666 ***	−1.248 ***	−50.898 ***
	(−1.196)	(−13.495)	(−3.406)	(−13.304)
N	28,558	28,558	28,558	28,558
Year	Yes	Yes	Yes	Yes
Industry	Yes	Yes	Yes	Yes
Adjusted R2	0.119	0.478	0.041	0.468

*, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively.

present the findings of the executive green cognition mechanism test. As shown in Column (1), the coefficient of Myopia is −0.316, which is significantly negative at the 10% level. This finding suggests that managerial myopia hinders corporate CID by reducing executive environmental awareness, supporting H2.

5.1.2. Green Innovation

As previously discussed, companies with shortsighted management tend to reduce their investment in green R&D [15], which limits their capability to optimize the allocation of production elements and improve green technology innovation [73] and eventually reduces corporate CID. Columns (3) and (4) of Table 9 report the regression results. The coefficient of management shortsightedness in Column (3) is −0.297, which is significant at the 5% level. This finding reveals that management shortsightedness hinders companies’ engagement in conducting environmental innovation activities; therefore, green innovation plays a mechanistic role in the relationship between management shortsightedness and CID. The finding supports H3.

5.1.3. Heterogeneity Analysis

To enrich the implications of our main study results, we conduct a heterogeneity analysis considering corporate ownership and industry to further investigate the functioning mechanism of the relationship between managerial myopia and CID.

5.1.4. Corporate Governance

Short-term management behavior in companies with inadequate governance structures has a higher probability of dominating corporate decision-making, but effective corporate governance can mitigate the negative impact of management myopia to a certain extent [74]. Therefore, we expected managerial myopia to have a more substantial detrimental effect on CID in companies with weak corporate governance. In practice, independent directors serve as a key supervisory mechanism in the corporate internal governance structure, which can effectively constrain opportunistic management behaviors, improve corporate transparency, and enhance the level of social responsibility disclosure [75]. When the number of independent directors on a company’s board is insufficient, there lacks an effective mechanism for checks and balances, and short-term management behavior is more likely to occur. Following Jin et al. [76], we use the ratio of independent directors to the total number of board members as a measure of corporate governance. Based on the median value of the proportion of independent directors, we split the sample into two groups: companies with higher proportions of independent directors, suggesting stronger governance, and those with lower proportions of independent directors, indicating weaker governance structure. Columns (1) and (2) in

Table 10. Results of heterogeneity tests.

Variables	(1)	(2)	(3)	(4)
	More Independent Director	Less Independent Director	Technology- Intensive	Non-Technology-Intensive
	CID	CID	CID	CID
Myopia	−3.527	−4.205 **	0.256	−7.889 ***
	(−1.394)	(−2.213)	(0.108)	(−3.991)
Size	2.900 ***	2.378 ***	2.807 ***	2.503 ***
	(9.868)	(10.512)	(11.076)	(9.639)
Roa	2.945 **	3.200 **	3.831 ***	2.657 *
	(2.197)	(2.465)	(3.209)	(1.859)
Lev	−1.853 **	−1.690 **	−1.378 *	−2.123 **
	(−2.046)	(−2.248)	(−1.738)	(−2.491)
Growth	−0.408 ***	−0.584 ***	−0.589 ***	−0.543 ***
	(−2.599)	(−4.205)	(−3.571)	(−4.091)
Board	−0.296	−1.891 *	−0.360	−0.568
	(−0.382)	(−1.769)	(−0.570)	(−0.838)
Dual	−0.072	0.145	−0.072	0.038
	(−0.288)	(0.666)	(−0.344)	(0.156)
Top1	0.033 *	−0.002	0.029 *	0.005
	(1.779)	(−0.131)	(1.733)	(0.339)
Mhold	3.610 ***	4.559 ***	4.726 ***	3.493 ***
	(4.003)	(4.946)	(5.626)	(3.533)
Ins	0.026 ***	0.043 ***	0.030 ***	0.042 ***
	(2.803)	(5.698)	(3.986)	(4.796)
Constant	−58.730 ***	−42.815 ***	−56.769 ***	−48.431 ***
	(−9.405)	(−8.287)	(−10.417)	(−8.707)
N	12,600	15,958	14,448	14,110
Year	Yes	Yes	Yes	Yes
Industry	Yes	Yes	Yes	Yes
Adjusted R2	0.439	0.467	0.465	0.466

*, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively.

present the heterogeneity analysis results. The coefficient of managerial myopia is not significant for companies with stronger governance structures, as shown in Column (1), but is significantly negative in Column (2). This result indicates that the inhibitory effect of managerial myopia on CID is more substantial in companies with weak corporate governance.

5.1.5. Corporate Industry

The inhibitory effect of management myopia on CID may vary for listed companies in different types of industries. Technology-intensive companies are more inclined to engage in long-term planning and technological innovation because of their rapid product and technology updates and large R&D investment [77]; thus, the inhibitory effect of managerial myopia may be weaker. In less technology-intensive companies, which have relatively lower industry competition and market attention, external supervision mechanisms are less effective in constraining management behaviors [78]; thus, managerial myopia is more likely to dominate business decision-making behaviors. Therefore, we perform a heterogeneity analysis based on industry and expect managerial myopia to have a more substantial detrimental effect on CID in non-technology-intensive companies than in technology-intensive industries. Columns (3) and (4) in Table 10 present the analysis results. The coefficient of managerial myopia is not significant for technology-intensive companies in Column (3) but is significantly negative in Column (4), indicating that the inhibitory effect of managerial myopia on CID is more substantial for non-technology-intensive companies.

6. Discussion and Conclusions

This study examines how managerial myopia affects CID, using a sample of Chinese A-share-listed companies for the period 2010–2023. It focuses on managerial myopia rather than broader management characteristics, using the frequency of short-term words in text analysis as a core proxy variable to accurately capture its dual characteristics of cognitive orientation and linguistic tendencies. This distinction is particularly important because previous studies often measure myopia using characteristic variables such as R&D expenditure or CEO age [53], but these indicators may not fully capture management’s short-term decision-making preferences. In contrast, text analysis can directly extract myopia-focused linguistic features from management’s publicly disclosed annual documents, reflecting managers’ focus on immediate returns while avoiding the limitations of a single financial metric. Furthermore, we use current short-term investment as a robust measure of managerial myopia to increase the reliability of our conclusions.

Baseline regression results show that higher levels of managerial myopia are associated with significantly lower corporate carbon disclosure. This finding aligns with previous research that short-term performance orientation leads management to exhibit avoidance tendencies in disclosing non-financial information [79], and it further supplements the cognitive drivers behind management environmental behavior [80]. This study verifies this conclusion in the Chinese institutional context, showing that managerial myopia is not only a problem at the financial decision-making level, but also has a systemic impact on corporate sustainable governance and information transparency. Additionally, our empirical results show that managerial myopia dampens companies’ motivation to disclose carbon emissions by reducing executives’ green awareness and corporate green innovation. Further analysis reveals that the impact of managerial myopia on CID is particularly pronounced for companies with weak corporate governance structures and companies that are not technology-intensive.

The findings of this study provide important empirical evidence for the relationship between management myopia and corporate CID in emerging countries. There are some significant implications. First, for investors and other interested parties, more attention should be paid to the long-term strategic goals of companies in terms of reducing carbon emissions and disclosing carbon information. Stakeholders should evaluate corporate value with respect to both short-term financial indicators and non-financial information such as environmental performance and carbon transparency in a firm’s corporate decision-making framework. In particular, an emphasis on long-term value can help alleviate managerial motivation to avoid CID due to short-term profit pressure and encourage companies to establish a more robust strategic plan for sustainable development. In addition, companies should strengthen their internal governance structure, improve decision-making and supervision mechanisms, and formulate rational strategic plans to constrain the adverse impact of shortsighted management behaviors on CID. Companies should also optimize the incentive mechanism for executives, incorporate carbon disclosure performance into their management performance evaluation system, and prompt managers to take responsibility for environmental performance and related information disclosure in addition to their pursuit of business financial performance. For regulators, binding regulations should be refined to shift carbon disclosure from an incentive-based to a mandatory approach. Companies should be required to disclose quantitative, comparable key carbon indicators and adopt standardized accounting standards. Furthermore, boards of directors should be encouraged to establish climate-related committees to oversee the company’s climate-related risks and carbon performance, and disclose the oversight process and results in annual reports.

Finally, this study has certain limitations. Additional research is necessary to address biases in text analysis arising from implicit or complex language, thereby improving the accuracy of managerial myopia measurement. Further research is also needed to determine how short-term and long-term word frequency can be simultaneously accounted for when measuring managerial myopia. In addition, it can further explore how the internal governance mechanism can be optimized through institutional arrangements and how companies can be encouraged to focus more on long-run sustainable development strategies. In addition, to make the research conclusions more universally applicable, we consider using English—an international common language—in the textual analysis of managerial myopia to further compare the governance effects of disclosures in English.