Assessing the Drivers of Corporate Sustainability Performance Disclosures Using the Global Reporting Initiative (GRI) G4 Framework

Abstract

The primary objective of this study is to analyze the factors influencing the corporate sustainability performance disclosures of companies listed on the Bombay Stock Exchange (BSE) using the Global Reporting Initiative (GRI) G4 framework. This research is based on a sample of 434 firms listed on the BSE from 2017 to 2022. According to the content analysis method, the disclosure score of 434 non-financial companies is 79% (approximately), suggesting that, on an average, the sample companies have revealed 79% of the GRI-specified elements in their sustainability reports. The outcomes of the regression models indicate that profitability, firm size, innovation, board size, gender diversity, sustainability committee, and industry type are major drivers of corporate sustainability performance disclosure. Furthermore, research identified significant differences in the determinants of such practices between high-polluting and low-polluting companies. This research aims to elucidate the intricate dynamics affecting corporate sustainability performance by examining a diverse array of concerns. It employs meticulous data analysis to identify critical elements influencing sustainability disclosure. These findings may assist corporate managers, investors, policymakers, and stakeholders in comprehending the critical aspects to consider when formulating strategies that promote sustainability and enhance long-term value maximization.

1. Introduction

Recent studies indicate that increasing environmental concerns and stakeholder demands for openness have rendered corporate sustainability performance disclosures (CSPD) essential for assessing an organization’s dedication to sustainable development (Lodhia et al. 2023; Bose et al. 2024). The significance of corporate sustainability performance (CSP) has markedly increased in the contemporary global business environment, propelled by a growing awareness of environmental, social, and governance (ESG) concerns (Poyser and Daugaard 2023). Global organizations are progressively adopting frameworks like the Global Reporting Initiative’s G4 guidelines to communicate their sustainability performance via reports, signifying a shift towards greater transparency and accountability in corporate conduct (Jeriji et al. 2023; Bose et al. 2024; Friske et al. 2023). Nevertheless, depending only on the annual report to evaluate the company’s overall performance has become a risky undertaking for any stakeholder (Arkoh et al. 2024). Moreover, governments, NGOs, investors, and other stakeholders are applying substantial pressure on enterprises to adeptly manage the adverse effects stemming from their operational activities. In response to this demand, firms began reconfiguring their business strategies by integrating corporate sustainability into their management processes and adopting sustainability reporting standards primarily under the GRI framework (Hasan et al. 2022).

Corporate sustainability is firmly established in developed countries, including France, Japan, Germany, the United States, and the United Kingdom. Conversely, the notion of sustainability reporting is somewhat embryonic in India, with most corporations beginning to report around 2008–2009 (Carrots and Sticks 2013). Consequently, the reporting rates were markedly elevated in affluent nations (such as Germany, Japan, the United States, the United Kingdom, and France) compared to developing nations (China, Bangladesh, Pakistan, India, and Indonesia) (Tilt et al. 2021). Policymakers and regulators are diligently formulating rules, regulations, and standards to enhance sustainability reporting, which is becoming increasingly essential for global efforts addressing environmental and social issues (Ben Fatma and Chouaibi 2021; Uyar et al. 2021), for instance, the Company Liability Acts of 2007 and 2012 in Indonesia. The firms Act of 2013 in India is a groundbreaking move globally, as it is the first to impose a mandatory corporate social responsibility expenditure requirement on firms. Additionally, under the Indian regulatory framework, the Securities and Exchange Board of India (SEBI) has mandated, since 2016, the incorporation of Business Responsibility Reports in the financial disclosures of the top 500 listed businesses. In the Asia–Pacific area, such regulations have been a catalyst for the ongoing increase in sustainability reporting (Carrots and Sticks 2016). KPMG’s (2011, 2015, 2019) study findings indicate that growing nations such as India, Indonesia, and Malaysia are at the forefront of sustainability reporting practices.

Recently, researchers have focused on understanding corporate sustainability dis-closure and its effects, especially on economic performance, resulting in ambiguous and contradictory findings (Mellahi et al. 2016). If engagement in corporate sustainability efforts does not lead to improved financial performance, it prompts us to enquire: what characteristics of corporate sustainability practices compel organizations to partake in such projects? Understanding the elements influencing sustainability initiatives would enhance our knowledge of the diverse approaches’ organizations take regarding involvement in corporate sustainability efforts. Despite substantial examination of this issue in recent years, the majority of studies have been conducted in Spain, Brazil, the UK, and the USA (Hahn and Kühnen 2013; McWilliams and Siegel 2001; Crisóstomo et al. 2019). CSP constitutes a holistic conceptual framework encompassing aspects of the economic, societal, and environmental spheres; nevertheless, scholars have concentrated their investigations on corporate sustainability by emphasizing merely one or two dimensions, such as the environmental (Andrikopoulos and Kriklani 2013; Moneva and Cuellar 2009) and social dimensions (Padgett and Galan 2010; Ortas et al. 2015). A restricted quantity of research initiatives has examined the comprehensive dimensions of business sustainability practices (Ben Fatma and Chouaibi 2021; Arkoh et al. 2024; Hasan et al. 2022).

In India, the domain of corporate sustainability reporting has been undergoing swift evolution (Narula et al. 2024). A number of companies at different phases of adopting sustainability reporting are listed on the Bombay Stock Exchange (BSE). The Indian government’s enactment of corporate social responsibility (CSR) via the Companies Act 2013 represented a notable progression, positioning India as the first nation to regulate CSR expenditures (Narula et al. 2024). The aforementioned move has necessitated India to improve its transparency concerning its social and environmental impact, in accordance with global standards. Furthermore, Indian companies are progressively acknowledging the significance of sustainability disclosures in augmenting their brand value and securing stakeholder trust (Oware and Worae 2023). SEBI is currently mandating the top 1000 listed companies, based on market capitalization, to comply with corporate responsibility and sustainability reporting guidelines. This strategy corresponds with global trends and guarantees that Indian businesses will maintain their strength and competitiveness in the international marketplace.

Oware and Worae (2023) contend that the Global Reporting Initiative (GRI) framework has not been used extensively in research on CSPD in India. Previous studies on CSPD in India are predominantly descriptive (Bhatia and Chander 2014), with a limited number examining its effect on corporate performance (Laskar and Maji 2016). Consequently, there is a notable gap in the current corpus of knowledge—a shortage in understanding the elements that affect CSPD within the Indian setting. The deficiency of study in this domain underscores the necessity for a comprehensive inquiry to identify and analyze the factors influencing CSPD within publicly traded companies in India. Following are the research objectives framed to fill the research gap:

• To evaluate the extent of CSPD of BSE-listed companies in India using the GRI framework.
• To determine the factors that affect the CSPD of BSE-listed companies in India.
• To investigate the differences in the CSPD of BSE-listed companies in India in relation to the corporate risk profile.

The current body of literature also indicates that the terms “corporate sustainability reporting/disclosure (CSPD)” and “corporate sustainability (CSP)” are frequently used interchangeably when the content analysis technique is implemented for the quantitative evaluation of CSPD (Laskar and Maji 2016).

The outcomes of the current study significantly enhance the domain of corporate sustainability reporting practices among enterprises listed on the BSE. This study offers significant insights on the degree of transparency and the determinants affecting these behaviors by analyzing a sample of 434 non-financial enterprises across a six-year period, from 2016–2017 to 2021–2022. The data indicate a favorable trend of heightened disclosure requirements across the sampled organizations, with an average disclosure level of approximately 79% of the sustainability report components mandated by the Global Reporting Initiative (GRI). This demonstrates the increasing commitment of the selected companies to deliver clear and transparent reports on their sustainability initiatives. Furthermore, the assessment recognizes numerous critical aspects that influence business sustainability reporting methods in India. Key determinants include profitability, business size, innovation, board size, gender diversity, the presence of a sustainability committee, and industry classification. These findings can aid governments and corporate leaders in improving their comprehension of sustainability reporting systems. Moreover, this study provides valuable insights by contrasting the reporting methodologies of companies operating in sectors with varying levels of pollution. These significant disparities underscore the necessity of customizing reporting methodologies to accommodate the unique characteristics and challenges encountered by various business sectors and organizations.

The remaining portions are structured as follows: Section 2 deals with the literature review and hypotheses development, followed by Section 3, which deals with the research methodologies. Section 4 is dedicated to corporate sustainability performance disclosure, followed by empirical findings in Section 5. Section 6 deals with the conclusion and managerial implication of this study, followed by study limitations and directions for future research work in Section 7.

2. Literature Review and Hypotheses Development

2.1. Theories Supporting Corporate Sustainability Reporting

Integrating stakeholder theory, legitimacy theory, and resource-based view theory is critical for driving corporate sustainability reporting strategies that suit the needs of modern business contexts. Stakeholder theory underscores the necessity for enterprises to understand and respond to stakeholder demands, a principle that directly impacts sustainability reporting. Organizations can augment their credibility and trustworthiness among stakeholders and the general public by establishing reporting mechanisms that integrate stakeholder perspectives, thereby exhibiting responsiveness, accountability, and transparency (Post et al. 2002).

Legitimacy theory underscores the importance of sustainability reporting in securing societal endorsement and maintaining an organization’s legitimacy. Organizations seek to improve their perceived legitimacy by transparently disclosing their sustainability goals, impacts, and performance metrics, thereby aligning their operations with social expectations and norms (Deegan 2002). Corporate sustainability reports serve as a mechanism for companies to demonstrate their commitment to social and environmental responsibility, thereby protecting their social license to operate and fostering confidence among stakeholders. Moreover, resource-based view theory offers significant insights into the strategic rationale for sustainability reporting methods. Hart (1995) asserts that businesses can enhance their long-term sustainability and competitiveness by identifying and utilizing diverse resources to cultivate distinctive skills. Companies can exhibit their potential to create shared value and tackle environmental and social challenges by highlighting their competencies, such as innovative technologies, strong corporate culture, and stakeholder collaborations, via sustainability reporting. An integrated approach to organizational management is enhanced by incorporating these theories into corporate sustainability reporting practices. This method considers stakeholder interests, the necessity of societal legitimacy, and the strategic allocation of resources for sustained value generation (Laskar 2018). Adopting these principles allows for companies to enhance their performance and resilience while positively impacting broader societal and environmental objectives.

2.2. Empirical Studies on the Determinants of Corporate Sustainability Performance Disclosure

2.2.1. Firm Size

Numerous researchers have asserted in their studies that large organizations regard corporate sustainability reporting as highly significant due to increased public scrutiny (Desai 2022). Large corporations are more involved in sustainability-related activities and reporting to establish a perception of legitimacy among stakeholders (Desai 2022). Ho and Taylor (2007) employed multiple regression analysis to investigate the factors influencing sustainability reporting in Japan and the United States, demonstrating a statistically significant positive correlation between business size and sustainability disclosure. This result is similar to the findings of Amran and Haniffa (2011) in developing countries, Desai (2022) in Indian firms, and Sun et al. (2022) in the context of China. Amran et al. (2014) identified a significant negative impact of business size on the disclosure of corporate sustainability practices, based on a study of 113 companies across 12 Asia–Pacific nations. Kiliç et al. (2015) further substantiated these findings inside the Turkish banking sector. Conversely, Mahmood et al. (2018) found no significant impact of firm size on sustainability reporting.

Crisóstomo et al. (2019) assert that larger enterprises engage with a broad array of stakeholders, resulting in a heightened feeling of accountability for economic, social, and governance issues. In this context, these factors are especially pertinent for larger enterprises, which must comply with ethical standards and incorporate advanced environmental measures. Based on this literature, the present study proposes that large-size firms are more committed to CSP, as detailed in the following hypothesis:

H1. 

Firm size positively influences corporate sustainability performance disclosure.

2.2.2. Profitability

Signaling theory posits that when enterprises’ profitability rises, corporate managers will want to transparently disseminate their sustainability reports to shareholders, with the objective of improving the management’s reputation (Crisóstomo et al. 2019). From a theoretical standpoint, scholars have sought to examine the relationship between profitability and increased disclosure. Isabel and Branco (2013) examined the elements influencing CSP within Brazilian enterprises. Their study revealed that the impact of a firm’s profitability on CSP was statistically significant and favorable. Multiple studies have also demonstrated the beneficial impact of profitability on sustainability disclosure (Orazalin and Mahmood 2020; Embuningtiyas et al. 2020; Sharma et al. 2020; Haladu and Bin-Nashwan 2022). In contrast to these findings, Girón et al. (2020) observed a detrimental effect of ROE on sustainability reporting in the contexts of Asia and Africa.

In contrast, researchers like Dissanayake et al. (2016) in the Sri Lankan context and Girón et al. (2020) in the wider contexts of Asia and Africa found no significant correlation between return on assets (ROA) and corporate social disclosure. Crisóstomo et al. (2019) reported analogous outcomes in their analysis of Brazilian panel data. The above literature relating to profitability and sustainability disclosure clearly indicates mixed results. However, based on the signaling theory perspective, the present study develops the following tentative hypothesis for empirical testing:

H2. 

Profitability positively influences corporate sustainability performance disclosure.

2.2.3. Leverage

Debt holders, as a significant stakeholder group, typically anticipate better returns on their investments in the firm, in addition to the repayment of their loans (Kuzey and Uyar 2017). Consequently, it requires the economic sustainability of enterprises while mitigating sustainability-related risks (Kuzey and Uyar 2017). Consequently, the extent of debt capital constrains management’s ability to allocate available free cash flows, leading to the presumption that debt holders anticipate the firm will invest these cash flows in ventures other than sustainability initiatives to secure improved returns alongside loan repayment. This discussion indicates a negative correlation between leverage and CSP. Andrikopoulos and Kriklani (2013) observed a negative correlation between leverage and corporate environmental disclosure in Denmark, whereas Desai (2022) reported similar findings for Indian corporations. Consequently, Shamil et al. (2014), studying 148 listed enterprises in Sri Lanka, and Crisóstomo et al. (2019), examining Brazilian corporations, determined that there is no substantial correlation between the two constructs. Given the absence of conclusive evidence regarding the impact of leverage on sustainability reporting, the subsequent tentative hypothesis has been formulated for two-tailed statistical testing:

H3. 

An association exists between leverage and corporate sustainability performance disclosure.

2.2.4. Innovation

From the resource-based view perspective, implementing corporate sustainability policies can provide enterprises with a sustainable competitive advantage and enable them to distinguish themselves from their market competition. McWilliams and Siegel (2001) assert that a corporation can achieve differentiation by committing resources to research and development, which may yield novel processes and products. Theyel (2000) examined US chemical companies and asserted that R&D investment was a significant catalyst for innovation in pollution management. Husted and Allen (2007) also confirmed the significant impact of R&D expenditure on environmental performance as a key element of corporate sustainability policies for Spanish enterprises. Brammer and Millington (2008) showed a positive association between investment in R&D and the implementation of business sustainability initiatives. Therefore, the following tentative hypothesis was formulated for statistical testing:

H4. 

R&D expenditure positively influences corporate sustainability performance disclosure.

2.2.5. Board Size

A substantial board size assists the business manager in mitigating agency conflict and disseminating signals to the broader stakeholder community. Consequently, a larger board is more inclined to enhance its sustainability disclosure (Fernández-Gago et al. 2018) to mitigate the managerial risk of societal boycott. Prior studies demonstrate a substantial positive correlation between board size and corporate sustainability disclosure, ascribed to the board’s diverse performance and recognition (Fernández-Gago et al. 2018). Fernández-Gago et al. (2018) indicated a substantial positive correlation between board size and CSR disclosure among Spanish listed companies, attributed to the board’s experience and expertise. Mahmood et al. (2018) established a positive and statistically significant effect of increased board size on comprehensive sustainability disclosure across enterprises in Pakistan, corroborating the findings of Sun et al. (2022) in China. Previous studies have observed a negative correlation between board size and sustainability reporting, suggesting that an increased number of directors may lead to inefficiencies in corporate management (Amran et al. 2014; Kiliç et al. 2015). Drawing on the aforementioned discourse and empirical findings, the current study formulated a provisional hypothesis for empirical testing:

H5. 

Board size positively influences corporate sustainability performance disclosure.

2.2.6. Board Independence

Boards with a greater proportion of independent directors exert pressure on management to disclose more information, thus reducing agency costs. According to Haniffa and Cooke (2005), independent directors function as accountability mechanisms, ensuring that corporations act in the interests of both shareholders and larger stakeholders. In the context of China, Sun et al. (2022) found no significant evidence of a correlation between board independence and CSR disclosure. In contrast, Barako et al. (2006) identified a negative association between board independence and voluntary disclosure in Kenyan companies, Haniffa and Cooke (2005) noted the same for Malaysian corporations, and Miras-Rodriguez and Di Pietra (2018) reported similar findings for BRICS countries. In contrast, Chau and Gray (2010) established a positive association between the ratio of independent directors and voluntary disclosures in Hong Kong corporations. The aforementioned research reveals a diverse empirical landscape concerning the relationship between corporate sustainability disclosure and board independence. Consequently, from a theoretical standpoint, the present study posits the following provisional hypothesis for empirical validation:

H6. 

Board independence positively influences corporate sustainability performance disclosure.

2.2.7. Gender Diversity

Gender diversity is a current subject of discussion that has gained traction in corporate governance studies. Ong and Djajadikerta (2018) empirically investigated the influence of governance features on sustainability reporting by analyzing corporations in Australia’s resources sector. Their research findings clearly confirmed a significant and favorable relationship between gender diversity and the reporting of sustainability practices. Vitolla et al. (2020a, 2020b) further illustrate the positive impact of female directors on corporate voluntary reporting. Haque and Jones (2020) assert that a board with increased female director representation correlates with enhanced biodiversity disclosure across European corporations. Conversely, Shamil et al. (2014) discovered a negative correlation between the two dimensions in a study of 148 publicly listed enterprises in Sri Lanka. Based on these literature reviews, the present study posits the following provisional hypothesis for empirical validation:

H7. 

Gender diversity positively influences corporate sustainability performance disclosure.

2.2.8. Chief Executive Officer (CEO) Duality

CEO duality occurs when the CEO simultaneously holds the position of chairperson inside the organization. This amalgamation of functions may compromise the board’s efficacy in supervising company sustainability disclosures (Li et al. 2008). The dual role of the CEO as chair of the board poses a danger of information concealment or manipulation, hence generating problems over transparency and accountability in sustainability reporting. Sun et al. (2022) emphasized that power concentration negatively impacts the voluntary disclosure procedures of Chinese firms, corroborating the conclusions of Huafang and Jianguo (2007) for listed Chinese corporations. Conversely, research conducted by Haniffa and Cooke (2002) on Malaysian enterprises and Barako et al. (2006) on Kenyan firms revealed a negligible correlation between dual leadership and voluntary disclosures. Jizi et al. (2014) observed a substantial positive effect of CEO duality on social responsibility disclosure within the US banking sector.

The aforementioned literature demonstrates inconclusive outcomes. Consequently, in accordance with agency theory, which suggests that CEO duality negatively impacts the board’s governance function and corporate disclosure, this study proposes the following tentative hypothesis for empirical validation:

H8. 

CEO duality negatively influences corporate sustainability performance disclosure.

2.2.9. Sustainability Committee

The board can create a sustainability committee by designating a manager to supervise all matters related to company sustainability. By forming this committee, the board guarantees a distribution of accountability and duty, promoting decentralization within the organization and enhancing contact with diverse stakeholder groups. This committee will engage in diverse sustainability initiatives that will enhance societal and environmental growth, consequently bolstering the firm’s image and legitimacy. Moreover, such committees can mitigate political costs by overseeing and regulating both the financial and non-financial dimensions of firms, including obstacles such as carbon price (Masud et al. 2018). Thus, establishing such a committee can be seen as an effective approach for controlling stakeholder interaction and assuring legitimacy. Amran et al. (2014) empirically established a favorable association between socially responsible committees and the quality of sustainability reporting in Asia–Pacific countries. This conclusion was corroborated by Mahmood et al. (2018) for Pakistani firms. Consequently, this study proposes the following preliminary hypothesis for empirical verification:

H9. 

Sustainability committees positively influence corporate sustainability performance disclosure.

2.2.10. Industry Type

According to legitimacy theory, numerous research works have identified industry type as a significant variable in elucidating the degree of sustainability reporting (Kuzey and Uyar 2017). Diverse companies across various industries participate in distinct activities. Manufacturing enterprises participate in a greater number of activities than service organizations. Upon completion of the final items, manufacturing enterprises must store them in the warehouse prior to dispatching to consumers. Service companies often have a lesser detrimental impact on the environment and society. Manufacturing enterprises are typically larger and involved in a broader range of operations than service companies (Kuzey and Uyar 2017). Consequently, based on legitimacy theory, manufacturing corporations are anticipated to provide greater disclosure of corporate sustainability information. Legendre and Coderre (2013) empirically demonstrated that enterprises sensitive to environmental issues are more inclined to publish sustainability-related information due to stakeholder pressure. This observation corresponds with the study by Shamil et al. (2014) regarding companies in Sri Lanka. Thus, the following two tentative hypotheses were developed for empirical testing:

H10. 

There is a significant difference in the corporate sustainability practices of companies between companies operating in high-risk industries and companies operating in low-risk industries.

H10a. 

There is a significant difference in the factors that drive corporate sustainability practices of companies between companies operating in high-risk industries and companies operating in low-risk industries.

3. Research Techniques and Procedures

3.1. Population and Sample of This Study

In this research, the top 500 companies listed on the Bombay Stock Exchange comprise the study population. The sample for this study includes all non-financial companies that have regularly issued sustainability or responsibility reports on their websites since the financial year 2016–2017. Financial companies were excluded from the study due to their lack of direct involvement in diverse environmental activities and potential misalignment with the sustainability reporting framework established by the Global Reporting Initiative (GRI). The total sample for this study, excluding financial companies, consists of 434 companies.

3.2. Source of the Data and Study Period

The present study covers a period of six years, i.e., from 2016–2017 to 2021–2022. The base year of the present study is 2016–17 because SEBI mandated the top 500 companies to publish their sustainability reports w.e.f. 31st March 20161. The pertinent secondary data were procured from the officially published annual reports, corporate sustainability reports, or business responsibility reports of the respective companies.

3.3. Measurements of the Variables

3.3.1. Dependent Variable

The dependent variable CSPD is assessed by content analysis of sustainability or responsibility reports in this study. Researchers have employed sustainability performance disclosure as a dependent variable to investigate the factors influencing sustainability reporting practices (Ho and Taylor 2007; Artiach et al. 2010; Crisóstomo et al. 2019).

Content Analysis Technique

A substantial focus of research currently pertains to the information presented in published annual reports or corporate responsibility reports. Consequently, scholars often utilize content analysis to meticulously, systematically, and objectively scrutinize the content of disclosures (Laskar 2022; Sun et al. 2022). Moreover, the GRI framework provides a collection of metrics for assessing CSPD. Research indicates that the GRI methodology is the most effective for assessing sustainability disclosure ratings (Laskar 2022; Sun et al. 2022). A considerable number of the sampled organizations have adopted the GRI framework to communicate their responsibility-related actions to various stakeholders. Consequently, the components of the GRI framework are utilized as the basis for analysis.

This study employs the current GRI sustainability reporting framework, G4, for content analysis. The latest GRI sustainability reporting framework, G4, consists of a total of 91 items, including 48 items related to social performance (16 for labor, 12 for human rights, 11 for local communities, and 9 for customer health and safety or product responsibility), 34 items for environmental performance, and 9 items for economic performance. We employed a binary method to ascertain the disclosure score, analogous to the approach utilized by these researchers. Items included in the GRI framework are marked as “1” if disclosed in the public report; otherwise, they are labelled as “0”. After obtaining the scores for each item, the sustainability performance disclosure index (CSPD) is calculated as follows:

$${\mathrm{C}\mathrm{S}\mathrm{P}\mathrm{D}}_{\mathrm{j}}={\displaystyle \frac{{\sum }_{\mathrm{i}=1}^{\mathrm{n}}{\mathrm{X}}_{\mathrm{i}\mathrm{j}}}{{\mathrm{m}}_{\mathrm{j}}}}$$

(1)

where ‘m_j’ is the maximum expected score, ‘j’ is the company, ‘i’ is the item, and ‘X_ij’ is coded as ‘1’ if the item is disclosed and ‘0’ otherwise.

3.3.2. Independent Variables

The independent variables used in this study are explained in

Table 1. Independent variable descriptions.

Variable	Measure
Firm Size (FS)	Natural logarithm of firm’s total assets
Profitability (ROA)	Net profit after tax divided by total assets
Leverage (DE)	Debt/equity ratio
Innovation (R&D)	R&D expenditure
Board Size (BS)	Total number of directors present in the board
Board Independent (BI)	Percentage of independent directors to the total number of directors
Gender Diversity (GD)	Percentage of female directors to the total number of directors
CEO Duality (CEOD)	Dummy variable—‘1’ if the CEO also holds the position of a chairperson and ‘0’ otherwise
Sustainability Committee (SC)	The number of directors present in the committee
Industry Type (INDU)	Dummy variable—‘1’ for high-risk companies and ‘0’ otherwise

.

3.3.3. Control Variables

Because the sample firms are among the top BSE companies, their firm value is expected to be high, requiring these companies to report more sustainability-related information. Consequently, company value is included as a control variable in this study, quantified by the market-to-book ratio (Laskar and Maji 2016, 2018). The market-to-book (MBR) ratio is calculated as the ratio of market value to book value of stock. The market value of stock is calculated by multiplying the outstanding shares by the current market price of equity at the conclusion of each fiscal year. Additionally, a one-year time lag between sustainability disclosure (CSPD_Lag) and independent auditor (INDA) are included as control variables in this study. The independent auditor variable is measured by the number of independent auditors involved in the audit committee.

3.4. Empirical Models

3.4.1. Panel Data Regression Models

In order to examine the determinants of corporate sustainability performance disclosure, the appropriate panel data regression model is employed. This study undertakes the two most widely used tests, the Breusch–Pagan test and Hausman, test to find out the appropriate panel data regression model. While the significant chi-square value of the Breusch–Pagan test advocates in favor of random effect model instead of pooled ordinary least square model, the significant chi-square value of the Hausman test indicates that fixed effect model is more appropriate than a random effect model.

The general form of the random effect regression model is

$${\mathrm{Y}}_{\mathrm{i}\mathrm{t}}={\mathrm{\beta }}_0+{\mathrm{\beta }}_1{\mathrm{X}}_{1\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_2{\mathrm{X}}_{2\mathrm{i}\mathrm{t}}+\dots \dots \dots +{\mathrm{\omega }}_{\mathrm{i}\mathrm{t}}$$

(2)

where ${\mathrm{X}}_{\mathrm{1,2},\dots }$ are the numbers of explanatory variables and ${\mathrm{\omega }}_{\mathrm{i}\mathrm{t}}={\mathrm{\epsilon }}_{\mathrm{i}}+{\mathrm{u}}_{\mathrm{i}\mathrm{t}}$. The usual assumptions of the error components model are ${\mathrm{\epsilon }}_{\mathrm{i}}~\mathrm{N}\left(0,{\mathrm{\sigma }}_{\mathrm{\epsilon }}^2\right)\mathrm{and}{\mathrm{u}}_{\mathrm{i}\mathrm{t}}~\mathrm{N}\left(0,{\mathrm{\sigma }}_{\mathrm{u}}^2\right).$

Again, the general form of the fixed effect regression model is

$${\mathrm{Y}}_{\mathrm{i}\mathrm{t}}=\left({\mathrm{\beta }}_0+{\mathrm{\alpha }}_{\mathrm{i}}\right)+{\mathrm{X}}_{\mathrm{i}\mathrm{t}}^{\prime }\mathrm{\beta }+{\mathrm{v}}_{\mathrm{i}\mathrm{t}}$$

(3)

where ${\mathrm{v}}_{\mathrm{i}\mathrm{t}}$ is the error component and α_i is the heterogeneity effect. Here, ${\mathrm{\beta }}_0+{\mathrm{\alpha }}_{\mathrm{i}}={\mathrm{\beta }}_{\mathrm{i}}\mathrm{and}{\mathrm{v}}_{\mathrm{i}\mathrm{t}}\backsim \mathrm{N}\left(0,{\mathrm{\sigma }}_{\mathrm{v}}^2\right).$ The following is the general form of the regression model (i.e., model 4), which is employed in this study to investigate the determinants of CSPD:

$$\begin{array}{cc}\hfill {\mathrm{C}\mathrm{S}\mathrm{P}\mathrm{D}}_{\mathrm{i}\mathrm{t}}={\mathrm{\beta }}_0+& {\mathrm{\beta }}_1{\mathrm{F}\mathrm{S}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_2{\mathrm{R}\mathrm{O}\mathrm{A}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_3{\mathrm{D}\mathrm{E}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_4{\mathrm{R}\&\mathrm{D}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_5{\mathrm{B}\mathrm{S}}_{\mathrm{i}\mathrm{t}}\hfill \\ & +{\mathrm{\beta }}_6{\mathrm{G}\mathrm{D}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_7{\mathrm{C}\mathrm{E}\mathrm{O}\mathrm{D}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_8{\mathrm{B}\mathrm{I}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_9{\mathrm{S}\mathrm{C}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_{10}{\mathrm{I}\mathrm{N}\mathrm{D}\mathrm{U}}_{\mathrm{i}\mathrm{t}}\hfill \\ & +{\mathrm{\beta }}_{11}{\mathrm{M}\mathrm{B}\mathrm{R}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_{12}{\mathrm{I}\mathrm{N}\mathrm{D}\mathrm{A}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_{13}{\mathrm{C}\mathrm{S}\mathrm{P}\mathrm{D}\_\mathrm{L}\mathrm{a}\mathrm{g}}_{\mathrm{i}\mathrm{t}}+{\mathrm{e}}_{\mathrm{i}\mathrm{t}}\hfill \end{array}$$

(4)

Models to Measure Relative Influence

The aforementioned regression models were employed to identify the factors influencing corporate sustainability performance disclosure for companies in both high-risk and low-risk industries.

To evaluate the relative impact of several determinants on CSPD among companies in high-risk and low-risk industries, we divided the entire sample into two categories. The classification was determined by the Comprehensive Environmental Pollution Index (CEPI) issued by the Central Pollution Control Board (CPCB). Upon partitioning the data into two subsets, we employed a dummy variable: ‘1’ for high-risk companies and ‘0’ for all others. We utilized these dummy variables to compute the interaction effect (i.e., the product of the dummy variable and each factor).

The subsequent regression models (i.e., model 5) are utilized to examine the relative influence:

$$\begin{array}{cc}\hfill {\mathrm{C}\mathrm{S}\mathrm{P}\mathrm{D}}_{\mathrm{i}\mathrm{t}}={\mathrm{\beta }}_0+& {\mathrm{\beta }}_1{\mathrm{F}\mathrm{S}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_2{\mathrm{D}\mathrm{x}\mathrm{F}\mathrm{S}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_3{\mathrm{R}\mathrm{O}\mathrm{A}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_4{\mathrm{D}\mathrm{x}\mathrm{R}\mathrm{O}\mathrm{A}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_5{\mathrm{D}\mathrm{E}}_{\mathrm{i}\mathrm{t}}\hfill \\ & +{\mathrm{\beta }}_6{\mathrm{D}\mathrm{x}\mathrm{D}\mathrm{E}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_7{\mathrm{R}\&\mathrm{D}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_8{\mathrm{D}\mathrm{x}\mathrm{R}\&\mathrm{D}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_9{\mathrm{B}\mathrm{S}}_{\mathrm{i}\mathrm{t}}\hfill \\ & +{\mathrm{\beta }}_{10}{\mathrm{D}\mathrm{x}\mathrm{B}\mathrm{S}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_{11}{\mathrm{G}\mathrm{D}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_{12}{\mathrm{D}\mathrm{x}\mathrm{G}\mathrm{D}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_{13}{\mathrm{C}\mathrm{E}\mathrm{O}\mathrm{D}}_{\mathrm{i}\mathrm{t}}\hfill \\ & +{\mathrm{\beta }}_{14}{\mathrm{D}\mathrm{x}\mathrm{C}\mathrm{E}\mathrm{O}\mathrm{D}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_{15}{\mathrm{B}\mathrm{I}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_{16}{\mathrm{D}\mathrm{x}\mathrm{B}\mathrm{I}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\beta }}_{17}{\mathrm{S}\mathrm{C}}_{\mathrm{i}\mathrm{t}}\hfill \\ & +{\mathrm{\beta }}_{18}{\mathrm{D}\mathrm{x}\mathrm{S}\mathrm{C}}_{\mathrm{i}\mathrm{t}}+{\mathrm{\omega }}_{\mathrm{i}\mathrm{t}}\hfill \end{array}$$

(5)

where D × FS is the interaction effect of FS and dummy; D × ROA is the interaction effect of ROA and dummy; D × DE is the interaction effect of DE and dummy; D × R&D is the interaction effect of R&D and dummy; D × BS is the interaction effect of BS and dummy; D × BI is the interaction effect of BI and dummy; D × GD is the interaction effect of GD and dummy; D × CEOD is the interaction effect of CEOD and dummy; D × SC is the interaction effect of SC and dummy. Dummy variable (D) represents ‘1’ for high-polluting companies and ‘0’ for low-polluting companies. The sign along with the level of significance of interaction variable indicate whether there is any significant difference in the factors that drives corporate sustainability practices of companies between companies operating in high-risk and low-risk industries.

4. Corporate Sustainability Disclosure

Figure 1 depicts the CSPD scores for prominent non-financial corporations, demonstrating an increasing trend in the CSPD information disseminated to a broader audience. The significant increase in disclosure scores in 2015–2016 corresponds with SEBI’s mandate for the top 500 listed businesses to report sustainability information. Remarkably, firms not only adhered to regulations but also showed outstanding levels of transparency. Analysis of the scores over several years indicates a steady enhancement from 68.96% in 2016–2017 to 89.90% in 2021–2022, reflecting significant progress in sustainability reporting. This disclosure pattern indicates a growing awareness among BSE-listed companies of the importance of sustainability reporting and highlights their dedication to transparency and responsiveness to stakeholder issues. The steadily rising average disclosure score of CSPD, in contrast to previous research, highlights the increasing importance and commitment of BSE-listed businesses to sustainability initiatives, enhancing stakeholder trust and attracting sustainability-focused investors.

Although Figure 1 clearly illustrates the average disclosure level for the studied organizations, it inadequately conveys a holistic perspective of overall CSPD. Figure 2 utilizes a box plot and whisker diagram to overcome this issue. The boxes for all years range from around 69% to 90%, suggesting that 50% of the sample organizations reported within this spectrum of GRI-specified items, signifying satisfactory performance. The median lines in the boxes indicate an average disclosure level of around 69% for 2016–2017, 75% for 2017–2018, nearly 73% for 2018–2019, and almost 89% for 2021–2022, aligning with the patterns depicted in Figure 1. The box plot distinctly illustrates several points situated below the lowest quartile and adjacent to the x-axis, signifying organizations with persistently inadequate disclosure over the years. Likewise, several data points over the upper quartile in the years 2016–2017, 2017–2018, 2018–2019, and 2020–2021 indicate corporations with notably high disclosure during those particular years, considered outliers.

5. Empirical Results

5.1. Descriptive Statistics

Table 2. Descriptive statistics.

	N	Minimum	Maximum	Mean	Std. Deviation	Skewness
CSPD	2604	33.292	93.178	78.992	7.491	−0.300
ROA	2604	−3.400	25.231	0.152	4.024	2.885
DE	2604	4.605	9.592	1.482	2.135	−0.447
FS	2604	2.300	15.820	10.235	1.629	−0.478
R&D	2604	2.810	10.240	5.154	2.068	0.041
BS	2604	7.000	27.000	13.050	2.908	0.927
BI	2604	9.000	30.000	18.476	6.742	0.674
GD	2604	0.000	40.000	10.389	4.832	2.018
CEOD	2604	0.000	1.000	0.290	0.454	0.929
SC	2604	4.000	9.000	5.802	1.121	1.849
INAD	2604	1.000	7.000	1.130	0.516	0.905
MBR	2604	1.605	6.638	2.694	1.594	−0.851

Source: computed by the author.

displays descriptive statistics, encompassing the mean, minimum, maximum, standard deviation, and skewness. The CSPD, with a mean of 78.99 percent, signifies that the sample companies revealed nearly 79 percent of the items specified in the GRI reporting framework. Although the sample companies are classified as high performers, the low average ROA (0.15) indicates subpar performance during the study period. The standard deviation (4.02) and skewness (2.885) of ROA indicate the existence of outliers. The debt-to-equity (DE) ratio averages 1.48, signifying that debt is 1.48 times greater than equity, accompanied by a low standard deviation and skewness. The mean board size (BS) is 13, indicating an average of 13 directors, accompanied by a low standard deviation and skewness. The mean value of independent directors (BI) is 18 percent, gender diversity (GD) is 10 percent, and CEO duality (CEOD) is 29 percent. The average of independent auditors is determined to be 1.13. The market-to-book ratio (MBR) is roughly 3, indicating that the market value of stock is threefold the book value. The sustainability/CSR committee (SC) typically comprises six members, exhibiting a low standard deviation and skewness, which signifies that the data are not widely dispersed.

5.2. Correlation Matrix

Table 3. Correlation matrix.

Variables	CSPD	ROA	DE	FS	MBR	R&D	BS	BI	GD	CEOD	SC	INDA	CSPD_Lag	VIF
CSPD	1.00													-
ROA	0.03	1.00												1.01
DE	−0.01	0.00	1.00											1.03
FS	0.07 **	−0.04	0.15 **	1.00										1.16
MBR	0.00	0.03	−0.01	0.23 **	1.00									1.07
R&D	0.03	−0.03	0.00	0.23 **	0.03	1.00								1.08
BS	0.00	0.01	−0.03	−0.01	0.01	0.02	1.00							1.34
BI	0.00	−0.01	−0.02	0.04	0.00	0.04 *	−0.30 **	1.00						1.12
GD	0.09 **	−0.01	0.01	0.06 **	0.05 *	−0.01	−0.22 **	0.07 **	1.00					1.06
CEOD	0.04 *	0.03	−0.01	−0.06 **	−0.06 **	0.07 **	−0.07 **	0.04	0.01	1.00				1.03
SC	0.02	−0.05 *	−0.06 **	0.09 **	0.08 **	0.04 *	0.32 **	0.00	−0.02	−0.09 **	1.00			1.16
INDA	0.00	0.00	−0.03	0.01	0.03	0.08 **	0.21 **	−0.02	−0.02	0.00	0.15 **	1.00		1.06
CSPD_Lag	0.15 **	0.02	0.00	−0.03	−0.01	−0.01	−0.02	−0.02	−0.05	0.04	−0.06	−0.04	1.00	1.01

Notes: ** indicates significant at 0.01 level and * indicates significant at 0.05 level by 2-tailed test. Source: computed by the author.

presents the correlation coefficients among the independent variables, primarily aimed at evaluating potential multicollinearity among them. The table indicates a negligible correlation among the independent variables, suggesting that multicollinearity is not a major issue in the current dataset. The correlation matrix presents the variance inflation factor (VIF) values for each independent variable, all of which are under 10. This result confirms the lack of multicollinearity among the independent variables, hence confirming the dataset’s robustness for subsequent analysis.

5.3. Regression Results

A panel data regression model has been employed to investigate the numerous factors influencing sustainability reporting practices in India, based on the findings of the Hausman and Breusch tests, which are presented in

Table 4. Fixed effect regression results.

	Coefficient	Std. Error	t-Ratio	p-Value
const	28.08	5.24	5.359	0.001	***
ROA	0.087	0.037	2.336	0.02	**
DE	−0.022	0.118	−0.186	0.852
FS	4.148	0.313	13.234	0.001	***
R&D	1.315	0.247	5.334	0.001	***
BS	0.297	0.113	2.626	0.009	***
BI	0.045	0.033	1.394	0.164
GD	0.496	0.052	9.471	0.001	***
CEOD	−0.441	2.566	−0.172	0.864
SC	1.027	0.236	4.35	0.001	***
INDUS	0.583	0.042	5.294	0.001	***
MBR	2.65	0.828	3.201	0.001	***
INDA	2.575	1.077	2.392	0.017	**
CSPD_Lag	0.278	0.019	15	0.001	***

Notes: Dependent variable = CSPD; F statistics = 2.72 ***; Breusch–Pagan test—chi-square = 53.9361 ***; Hausman test—Chi-square = 1157.85 ***; R² = 0.494. *** and ** indicate significance at 1% and 5% levels, respectively. Source: computed by the author.

. Given that both the Breusch–Pagan test and Hausman test produced statistically significant outcomes, we employed a fixed effects regression model for our dataset. The regression analysis in Table 4 demonstrates that firm size (FS) has a positive and statistically significant correlation at a 1 percent significance level. The aforementioned conclusion indicates that a company’s size considerably influences sustainability reporting practices in India. The observed beneficial impact of FS on CSPD corresponds with the results of previous research by Amran and Haniffa (2011), Crisóstomo et al. (2019), Sun et al. (2022), and Desai (2022). Therefore, alternative hypothesis (H1) is considered valid. The regression analysis reveals that profitability, measured by return on assets (ROA), is both positive and statistically significant at the 5 percent level. The effect of ROA on CSPD in this study aligns with the findings of other researchers (Embuningtiyas et al. 2020; Sharma et al. 2020; Haladu and Bin-Nashwan 2022). Therefore, alternative hypothesis (H2) is accepted.

Table 4 clearly indicates that the innovation measure, as determined by R&D expenditure, is both positive and statistically significant at the 1 percent level. The beneficial impact of R&D expenditure on CSPD signifies that innovation is crucial for sustainability disclosure. The favorable result of innovation affecting CSPD in this study aligns with the findings of previous research (Husted and Allen 2007; Brammer and Millington 2008). According to the regression results, we accept our alternative hypothesis (H4). The data also indicate that the coefficient for board size (BS) is significantly positive at the 1 percent level, implying a beneficial effect of board size on sustainability reporting standards. This discovery is consistent with the results of previous research studies (Mahmood et al. 2018; Fernández-Gago et al. 2018; Sun et al. 2022). As a result, alternative hypothesis (H5) is accepted.

Gender diversity (GD) is identified as a positive and statistically significant quality of corporate governance at the 1 percent level. The findings on gender diversity suggest that the inclusion of female directors on boards positively impacts sustainability reporting practices, as they contribute varied perspectives and experiences, leading to more thorough and precise sustainability disclosures. This result aligns with the findings of prior studies such as those by Ong and Djajadikerta (2018), Haque and Jones (2020), and Vitolla et al. (2020a, 2020b). Consequently, alternative hypothesis (H7) is adopted.

The regression results indicate that the coefficient for the sustainability committee (SC) is positive and statistically significant at the 1 percent level. The beneficial influence of the sustainability committee suggests that it is a crucial element influencing sustainability reporting procedures, as this committee is tasked with overseeing the company’s sustainability strategy, policies, and practices. Prior research has documented analogous results (Masud et al. 2018; Mahmood et al. 2018; Amran et al. 2014). In light of the regression results, we adopt alternative hypothesis (H9). Nonetheless, we identified that certain characteristics, such as leverage (DE), board independence (BI), and CEO duality (CEOD), are inconsequential. Furthermore, we observed that the impact industry (INDUS) exhibits a markedly positive effect at 1 percent, signifying that the kind of industry substantially influences corporate sustainability reporting practices in India. Consequently, we accept hypothesis (H10).

The empirical evidence concerning the impact of firm size, profitability, innovation, board size, gender diversity, existence of sustainability committees, and industry classification on corporate sustainability reporting can be theoretically substantiated by stakeholder theory, legitimacy theory, and the resource-based view. Stakeholder theory posits that larger corporations with substantial resources are more inclined to undertake sustainability reporting to manage relationships with various stakeholders, resolving their concerns and preserving competitive advantages. Legitimacy theory asserts that lucrative and innovative firms endeavor to exhibit compliance with public standards via sustainability reporting, thereby augmenting their legitimacy and obtaining their social license to operate. From a resource-based viewpoint, elements such as board size, gender diversity, and the existence of sustainability committees signify a firm’s internal competencies and strategic direction, impacting its capacity to manage resources effectively and generate sustainable value. These theoretical frameworks collectively reinforce the empirical findings, clarifying the motivations and mechanisms underlying corporate sustainability reporting practices.

Table 4 further illustrates that the independent auditor (INDA), utilized as a control variable, is highly positive at the 5 percent level. We also discovered that the effect of MBR is significantly positive at 1 percent, indicating that companies with advantageous market-to-book ratios are frequently seen more favorably by investors and stakeholders, as they are perceived to possess better potential for growth and profitability. Furthermore, we observe that the effect of a one-year time lag in sustainability disclosure is notably beneficial at the 1 percent level.

The regression table indicates that the observed R2 is adequate, and the F-statistic at the 1% significance level demonstrates that the regression model is statistically significant, with the explanatory factors collectively related to the dependent variable. Consequently, the results seemingly support the adequacy of the current regression model. Nonetheless, a crucial requirement is that the residuals must exhibit a normal distribution. To assess the normality of residuals, we generated the normal curve and the quantile–quantile (Q-Q) plots of the residuals, illustrated in Figure 3 and Figure 4, respectively. The Q-Q plot of residuals reveals the existence of outliers at both extremes of the distribution’s tails. Likewise, the normal distribution indicates the presence of a limited number of outliers. Consequently, to enhance the robustness of the regression results, we employed robust standard errors.

Table 5. Fixed effect regression results.

	Coefficient	Robust Std. Error	t-Ratio	p-Value
const	28.08	12.051	2.33	0.020	**
ROA	0.087	0.018	4.87	0.000	***
DE	−0.022	0.195	−0.1126	0.910
FS	4.148	0.951	4.36	0.000	***
R&D	1.315	0.357	3.686	0.000	***
BS	0.297	0.184	1.611	0.021	**
BI	0.045	0.043	1.047	0.296
GD	0.496	0.084	5.895	0.000	***
CEOD	−0.441	2.873	−0.1534	0.878
SC	1.027	0.317	3.243	0.001	***
INDUS	0.583	0.053	4.122	0.001	***
MBR	2.65	1.279	2.073	0.039	**
INDA	2.575	1.101	2.338	0.020	**
CSPD_Lag	0.278	0.016	17.6575	0.000	***

Notes: Dependent variable = CSPD; F statistics = 2.72 ***; Breusch–Pagan test—chi-square = 53.9361 ***; Hausman test—chi-square = 1157.85 ***; R² = 0.494. *** and ** indicate significance at 1% and 5% levels, respectively. Source: computed by the author.

presents the results of the robust standard error analysis. The regression model employing robust standard errors mitigates the assumptions of independent and identically distributed residuals (White 1980). The calculated robust standard errors in Table 5 corroborate the findings of the standard errors in Table 4, confirming the reliability of the results.

5.3.1. Robust Analysis

The above analysis was carried out using dynamic panel data analysis using a fixed effects model. This methodology addresses unobservable individual heterogeneity (time-invariant features), although it raises substantial concerns about potential bias arising from the endogeneity of lagged dependent variables. As a result, this may result in estimations that are biassed and inconsistent. To further substantiate the conclusions presented in the preceding section, we perform a robustness assessment utilizing a two-step system-generalized method of moments (system GMM) model estimator (i.e., model 6) to address endogeneity concerns (Arellano 2002). The general structure of the model is presented below:

$${\rho }_{i,t}={\alpha }_{i,t}+\pi {\phi }_{i,t-1}+\sum _{n=1}^n{\beta }_n{\gamma }_{i,t}^n+\sum _{k=1}^k{\beta }_k{\vartheta }_{i,t}^k+{\omega }_{i,t}+{\epsilon }_{i,t}$$

(6)

where ‘t’ is the time and ‘i’ is the firm. ${\epsilon }_{i,t}$ and ${\omega }_{i,t}$ are the idiosyncratic error and firm-specific unobserved effect, respectively; ${\vartheta }_{i,t}^k$ represents all the control variables; and ${\phi }_{i,t-1}$ is the time lag value of the dependent variable. Finally, ${\gamma }_{i,t}^n$ represents all the independent variables.

The results of the system GMM model are displayed in

Table 6. System GMM results.

Variables	Coefficient		Z-Stats.
ROA	0.215		1.660 *
DE	0.560		2.940 **
FS	1.609		2.440 **
R&D	0.750		1.830 *
BS	0.185		2.03 **
BI	0.735		1.200
GD	0.042		1.710 *
CEOD	0.016		0.550
SC	2.766		2.040 **
INDUS	1.735		2.080 **
MBR	2.288		2.000 **
INDA	0.026		1.191
CSPD_Lag	1.539		2.060 **
Const.	0.844		2.780 ***
Sargan test (p-value)		25.660 (p = 0.338)
Hansen test (p-value)		90.72 (p = 0.154)
AR(1): First-order autocorrelation test		−0.59 (p = 0.187)
AR(2): Second-order autocorrelation test		−1.14 (p = 0.139)
Wald (ϰ2)		250.21 ***

Note: ***, **, and * indicate significance at 1, 5, and 10%, respectively. Dependent variable: CSPD. Source: computed by the author.

. The results of the system GMM estimation indicate that BS, DE, FS, SC, and INDUS are positive and statistically significant at the 5% level. R&D, ROA, and GD are similarly observed to be beneficial and statistically significant at the 10% level. These reveal that BS, FS, SC, INDUS, R&D, ROA, and GD are key determinants of corporate sustainability reporting practices in India. This result aligns with the findings of the fixed effect model presented in Table 4 and Table 5. According to the system GMM estimation, DE is also an important determinant of corporate sustainability reporting methods in India. It is noted that both MBR and CSPD_Lag are positive and statistically significant at the 5% level among the control variables.

The Sargan test presented in Table 6 indicates no association between the residuals and the instruments. We observed that both the Arellano–Bond first- and second-order autocorrelation tests, AR(1) and AR(2), are insignificant, indicating a lack of autocorrelation. The Wald chi-square value signifies the prediction efficacy of the current models. Consequently, we can ascertain that our fixed regression findings align with the system GMM outcomes. Consequently, our findings are robust and reliable for decision-making, and we accept hypotheses H1, H2, H3, H4, H5, H7, H9, and H10.

5.3.2. Relative Impact

Model (5) is utilized to investigate the existence of substantial differences in the factors influencing CSPD across organizations in high-risk and low-risk industries.

Table 7. Dynamic fixed effects regression results: relative impact.

	Coefficient	Std. Error	Robust Std. Error	t-Ratio	p-Value
const	21.528	5.327	4.042	0.000	***
ROA	0.067	0.039	1.746	0.081	*
DxROA	0.826	1.547	2.1664	0.030	**
FS	2.915	0.389	7.491	0.000	***
DxFS	3.528	0.646	5.462	0.000	***
DE	−0.192	0.155	1.242	−0.214
DxDE	0.414	0.238	1.141	0.282
RD	1.245	0.358	3.481	0.001	***
DxRD	0.999	0.493	0.329	0.742
BS	0.725	0.174	4.158	0.000	***
DxBS	0.759	0.229	3.312	0.001	***
BI	0.051	0.048	1.066	0.287
DxBI	−0.000	0.065	0.001	−0.999
GD	0.434	0.072	6.009	0.000	***
DxGD	0.344	0.104	1.651	0.099	*
CEOD	1.501	3.174	0.473	0.636
DxCEOD	−6.814	5.413	1.259	−0.208
SC	1.148	0.348	3.304	0.001	***
DxSC	2.398	0.471	0.065	0.949
MBR	2.405	0.822	2.926	0.004	***
INDA	2.317	1.070	2.166	0.030	**
CSPD_Lag	0.274	0.018	14.860	0.000	***

Notes: Dependent variable = CSPD; F statistics = 2.72 ***; Breusch–Pagan test—chi-square = 54.399 ***; Hausman test—chi-square = 1234.62 ***; R² = 0.395045. *, ** and *** indicate significance at 10%, 5% and 1% levels, respectively. Source: computed by the author.

illustrates the results of the relative impact regression model. Table 7 illustrates that the interaction effect (i.e., DxROA) is significantly positive at the 5 percent level, indicating that the impact of profitability on CSPD practices is considerably more pronounced for high-polluting firms than for their low-polluting counterparts.

The DxFS is significantly positive at the 1 percent level after accounting for the influence of FS, suggesting that large, high-polluting enterprises are more likely to report on sustainability practices than their low-polluting counterparts. After accounting for the influence of BS, DxBS is significantly positive at the 1 percent level, indicating that the board size of high-polluting firms has a greater relative impact than that of low-polluting companies. The relative effect of DxGD is positive and statistically significant at 10 percent, suggesting that the gender diversity in high-polluting companies influences corporate sustainability policies more than in low-polluting organizations. The interaction model indicates a substantial disparity in the factors influencing corporate sustainability reporting methods between high-risk and low-risk organizations. Consequently, we accept hypothesis H10a of our current investigation. The influence of variables such as return on assets (ROA), board size (BS), gender diversity (GD), and firm size (FS) on corporate sustainability reporting practices is more pronounced in high-polluting companies than in low-polluting companies, owing to the increased environmental and stakeholder scrutiny these firms encounter.

6. Conclusions and Managerial Implications of This Study

The primary objective of this research is to assess the extent of disclosure and analyze the determinants influencing corporate sustainability reporting practices across enterprises listed on the Bombay Stock Exchange (BSE). This study analyses 434 non-financial firms over a six-year period, spanning from 2016–2017 to 2021–2022. The assessment of CSPD is performed by content analysis, employing the Global Reporting Initiative (GRI) reporting framework (G4) as the basis for this research. The overall disclosure rate of 434 non-financial organizations is about 79%, indicating that, on average, the sampled firms have disclosed 79% of the items required by the GRI in their sustainability reports. There is a consistent rise in the disclosure procedures of Indian corporations. Utilizing the dynamic fixed effect regression model, we identify profitability, company size, innovation, board size, gender diversity, sustainability committee, and industry type as major drivers of corporate sustainability reporting practices among Indian firms listed on the BSE. Consequently, we accept H1, H2, H4, H5, H7, H9, and H10. Furthermore, to ascertain any significant differences in the variables of corporate sustainability reporting practices across high-polluting and low-polluting corporations, we employ an interaction effect model. According to the interaction effect model, a considerable disparity exists in the determinants of corporate sustainability reporting practices between high-polluting and low-polluting enterprises. Consequently, we endorse H10a. We discovered that profitability, board size, firm size, and gender diversity had a more substantial impact on the corporate sustainability reporting practices of high-polluting corporations compared to low-polluting companies.

This study’s outcome offers crucial insights for corporate managers concerning sustainability performance. The emphasized determinants—profitability, gender diversity, business size, innovation, board size, sustainability committee, and industry type—underscore the essential elements affecting sustainability reporting methods. Managers can utilize these findings to design strategies that enhance their company’s sustainability practices. Highlighting profitability and innovation as essential elements while considering board size and gender diversity within the leadership team can improve a holistic strategy for sustainability. Establishing and nurturing sustainability committees can improve organizations’ efficacy in achieving sustainability objectives. Industry type considerations provide a context-specific viewpoint, aiding managers in aligning sustainability goals with sector-specific challenges and opportunities.

This research provides essential insights for policymakers, facilitating the formulation of laws and incentives that promote company sustainability. This may involve incentivizing investments in research and development for innovation, fostering gender diversity in leadership positions, and enabling the establishment of effective sustainability committees. Policymakers should tailor policies to address the specific requirements of distinct industries, acknowledging that diverse sectors may require varying sustainability approaches. This study’s conclusions offer policymakers evidence-based recommendations for fostering an environment conducive to sustainable business practices.

The sociological implications of this work are substantial. This research analyses factors influencing CSPD, promoting more responsible and accountable corporate practices. By emphasizing profitability, innovation, gender diversity, and sustainability committees, businesses can improve their financial performance and societal well-being. Enhanced engagement to sustainable practices can lead to reduced environmental consequences, enhanced social equity, and greater corporate accountability. Furthermore, comprehending industry-specific variables highlights the imperative for a comprehensive approach for sustainability across all sectors. This study ultimately fosters a sustainable and inclusive business environment by aligning corporate actions with society needs and aspirations. While this empirical research is focused on the Indian context, the findings offer valuable insights with potential applications for business managers worldwide. Understanding the factors influencing corporate sustainability reporting in India could provide a reference point for managers in other countries for comparison and reflection. Understanding the importance of firm size and profitability may prompt managers globally to assess how their company’s resources and financial performance influence their sustainability reporting practices. Understanding the impact of innovation, board size, gender diversity, and the presence of sustainability committees may encourage managers to evaluate their organizational structures, governance practices, and diversity initiatives to enhance their sustainability reporting efforts. Despite geographical variations in industry classification, the core principles of stakeholder involvement, legitimacy, and resource management are globally relevant to corporate sustainability reporting standards. Thus, the findings from the Indian context may serve as a standard for managers worldwide to improve their sustainability reporting methods, augment transparency, and demonstrate their commitment to sustainable business practices.

7. Limitations and Directions for Future Research Work

This study provides valuable insights into the factors influencing CSPD through the GRI G4 framework; nevertheless, it has certain limitations. Initially, it emphasizes a narrow spectrum of CSPD factors, possibly excluding other pertinent determinants like ownership structure, government regulations, and market regulations, which could also substantially affect CSPD practices. Secondly, this study exclusively utilizes the GRI G4 framework for evaluating disclosures, which restricts its relevance to alternative frameworks that might encompass various aspects of sustainability performance. This study also fails to examine cross-country variations, which could enhance understanding of CSPD practices in different regulatory and cultural contexts.

Future research may address these limitations by investigating additional factors, including ownership structure, government policies, and market regulations, to achieve a more comprehensive understanding of CSPD practices. Using alternative frameworks like the Carbon Disclosure Project and the United Nations Global Compact could enhance content analysis and provide a more comprehensive perspective on sustainability disclosures. Cross-country analyses may provide insights into the distinct determinants of CSPD practices across various regions and regulatory environments. The broadened scope would yield additional insights into the diverse factors influencing CSPD, thereby improving the generalizability of findings and contributing to a more comprehensive understanding of CSPD practices on a global scale.