Ethical Leadership and Its Impact on Corporate Sustainability and Financial Performance: The Role of Alignment with the Sustainable Development Goals

Abstract

This study examines the influence of ethical leadership on corporate sustainability and financial performance, highlighting the moderating effect of firms’ commitment to the United Nations Sustainable Development Goals (SDGs). Utilizing panel data from 420 automotive companies spanning 2015 to 2024, the analysis applies the System Generalized Method of Moments (GMM) to control for endogeneity and unobserved heterogeneity. All data were gathered from the Refinitiv Eikon Platform (LSEG) and annual reports. Panel GMM regression is used to estimate the relationship to deal with the endogeneity problem. The results reveal that ethical leadership significantly improves corporate sustainability performance—measured by ESG scores from Refinitiv Eikon and Bloomberg—as well as financial indicators like Return on Assets (ROA) and Tobin’s Q. Additionally, firms that demonstrate breadth (the range of SDG-related themes addressed), concentration (the distribution of non-financial disclosures across SDGs), and depth (the overall volume of SDG-related information) in their SDG disclosures gain greater advantages from ethical leadership, resulting in enhanced ESG performance and higher market valuation. This study offers valuable insights for corporate leaders, policymakers, and investors on how integrating ethical leadership with SDG alignment can drive sustainable and financial growth.

1. Introduction

In today’s fast-changing business environment, leadership within the global automotive industry is experiencing profound transformation. Traditional approaches that focused primarily on financial performance and maximizing shareholder value are increasingly giving way to more comprehensive strategies that embed sustainability into core operations. This evolution underscores a growing understanding that lasting financial and non-financial success in the automotive sector is closely tied to sustainability performance, encompassing environmental stewardship, social responsibility, and sound governance (ESG) practices. Ethical leadership—grounded in integrity, fairness, transparency, and accountability—has become essential to advancing both sustainability goals and financial results across the industry [1].

The critical role of ethical leadership in the automotive industry has been underscored by a series of high-profile scandals that have severely impacted the reputation and financial health of major companies. One of the most prominent cases is the Volkswagen emissions scandal, in which the company deliberately manipulated emissions tests to appear more environmentally compliant. Similarly, the Takata airbag crisis—marked by falsified safety data and defective airbags—triggered the largest recall in automotive history and resulted in multiple injuries and fatalities, ultimately leading to Takata’s bankruptcy. Nissan also faced a major setback when former CEO Carlos Ghosn was accused of financial misconduct, including underreporting earnings and misusing corporate resources, eroding investor confidence, and tarnishing the brand’s reputation. These incidents highlight how the absence of ethical leadership can drive decisions focused on short-term gains at the expense of long-term sustainability and corporate integrity, with severe consequences for financial performance and market trust [2].

Ethical leadership extends beyond mere compliance, creating a moral culture that prioritizes sustainable practices. Theories such as Transformational Leadership and Social Learning demonstrate that ethical leaders inspire their organizations to embrace sustainability [3]. Likewise, stakeholder theory emphasizes that ethical leaders effectively balance the interests of diverse stakeholders, strengthening relationships and promoting long-term sustainable success [4].

Recent research has increasingly underscored the connection between ethical leadership, sustainability performance, and financial results. For example, [5] found that ethical leadership strengthens organizational commitment and curbs unethical behavior, fostering more sustainable business practices. Similarly, [6] showed that ethical leadership enhances corporate transparency, a key factor in maintaining stakeholder trust and achieving long-term financial success. Sustainability performance, as reflected in ESG factors, signals a firm’s commitment to responsible practices and often correlates with stronger financial outcomes [7]. Strong sustainability performance is often linked to better financial outcomes, as stakeholders increasingly demand accountability on issues such as climate change and social inequality [8]. Ethical leadership plays a pivotal role in advancing sustainability, driving initiatives like emissions reduction and resource conservation [9].

The link between ethical leadership and firm performance has been widely debated. While some studies indicate a positive correlation, others argue that the costs associated with ethical practices can diminish short-term profitability [10]. Advocates contend that ethical behavior is not only the right thing to do but also yields long-term financial benefits. Ethical leaders are better positioned to attract top talent, strengthen stakeholder relationships, and enhance their firm’s reputation, all of which support stronger financial performance [11]. Empirical research has also demonstrated the positive impact of ethical leadership on financial results. For instance, [12] found a clear link between corporate social responsibility (CSR) and improved financial outcomes [7].

However, not all studies have identified a positive relationship between ethical leadership and financial performance. Some scholars argue that the costs of adopting ethical practices—such as investing in sustainable technologies or ensuring fair labor standards—can reduce short-term profitability [13]. This mixed evidence highlights an opportunity to further investigate both the financial and non-financial impacts of ethical leadership. Moreover, existing research has yet to fully examine how contextual factors like industry characteristics, firm size, and regulatory environments shape this relationship, underscoring the need for more comprehensive studies to explore these variables [7].

The United Nations’ SDGs offer a global framework for tackling some of humanity’s most urgent challenges, including poverty, inequality, climate change, and environmental degradation [14]. Established in 2015, as shown in Appendix A the 17 SDGs outline ambitious objectives aimed at creating a more sustainable and equitable world by 2030. For businesses, the SDGs present both a responsibility and an opportunity to support global sustainability efforts while strengthening their long-term resilience. Companies that align their strategies with the SDGs signal a commitment to sustainability that extends beyond basic regulatory compliance. By embedding the SDGs into their core operations, firms can help advance these global goals while improving their sustainability performance and enhancing their corporate reputation [15].

This study investigates the moderating role of SDG orientation in the relationship between ethical leadership and performance outcomes. Specifically, we assess whether firms with a stronger alignment to the SDGs experience a more pronounced positive impact of ethical leadership on both sustainability performance and financial results. Through this analysis, we aim to deepen understanding of how ethical leadership can advance sustainable and financial objectives within the context of a global sustainability framework.

The primary objective of this study is to examine the impact of ethical leadership on sustainability performance and corporate financial performance, with a particular emphasis on the moderating role of a firm’s orientation toward the SDGs. Specifically, we aim to answer several key research questions: (1) How does ethical leadership affect sustainability performance? (2) In what ways does ethical leadership influence corporate financial performance? (3) How does a firm’s alignment with the SDGs moderate these relationships? By exploring these questions, this study seeks to enrich the literature on ethical leadership, sustainability, and financial outcomes. Although prior research has increasingly highlighted the effects of ethical leadership on organizational performance, the moderating role of SDG orientation has received limited attention. This study aims to fill this gap by providing empirical evidence on how a firm’s commitment to the SDGs can strengthen the impact of ethical leadership in driving both sustainable practices and improved financial results.

This study employs a mixed-methods approach, combining panel data analysis of 420 automotive firms spanning the period from 2015 to 2024. First, a dedicated set of indicators was developed to evaluate firms’ alignment with the United Nations’ SDGs as shown in Appendix A. Content analysis of non-financial reports was conducted to measure SDG orientation using three dimensions: depth, capturing the extent of SDG-related disclosure; breadth, indicating the range of SDG themes addressed; and concentration, assessing the balance of information across different SDGs. Second, the System Generalized Method of Moments (GMM) was applied to perform a longitudinal quantitative analysis, examining how SDG orientation moderates the relationship between ethical leadership and corporate outcomes.

The findings demonstrate that ethical leadership positively influences both corporate sustainability and financial performance, with all dimensions of SDG orientation—depth, breadth, and concentration—significantly moderating this relationship. This study contributes to the literature by developing a new approach to evaluate firms’ alignment with the SDGs of the 2030 Agenda. The SDG framework establishes a shared vocabulary for understanding corporate sustainability practices. Furthermore, non-financial disclosures play a vital role in integrating sustainability principles into corporate strategy. This paper also identifies lessons learned, highlights research gaps, and proposes an agenda for future research.

The paper is structured as follows: Section 2 covers the literature review and hypothesis development, Section 3 details the methodology, Section 4 presents the results, and Section 5 and Section 6 offer discussion, conclusions, and future research directions.

2. Literature Review

2.1. The Direct Relationship Between Ethical Leadership and Sustainability Performance

According to Resource-Based View (RBV) theory, a firm’s competitive advantage stems from unique resources and capabilities that are valuable, rare, inimitable, and non-substitutable [16]. Within this framework, ethical leadership represents a critical intangible resource. Ethical leaders foster a corporate culture that emphasizes sustainability, driving practices that minimize environmental impact, advance social equity, and uphold ethical standards. These sustainability-oriented practices are increasingly recognized as valuable and rare assets that can set a firm apart from its competitors [16].

By embedding sustainability at the core of a firm’s strategy, ethical leadership strengthens the organization’s capacity to meet regulatory requirements, address stakeholder expectations, and capitalize on emerging market opportunities. This commitment to sustainability not only reduces risks related to environmental and social challenges but also enhances the firm’s reputation, making it more appealing to both consumers and investors [7]. Recent research has shown that ethical leadership plays a significant role in driving sustainability performance, particularly in industries with substantial environmental impacts [6,17,18]. In this context, ethical leadership functions as a critical resource that enables firms to achieve superior sustainability outcomes.

The Resource-Based View (RBV) posits that a firm’s competitive advantage arises from its distinctive internal resources and capabilities, which must be valuable, rare, inimitable, and non-substitutable [16,19]. Within this framework, ethical leadership represents a critical intangible resource that shapes organizational culture and promotes trust, integrity, and accountability [5,19]. In the automotive sector, ethical leaders champion sustainable initiatives such as reducing carbon emissions and implementing green technologies, aligning the firm’s operations with global environmental standards [6,20]. This alignment not only mitigates regulatory risks but also strengthens brand equity and market positioning, making ethical leadership a strategic asset that is difficult for competitors to imitate [21]. Moreover, ethical leadership fosters employee engagement and innovation, both of which are essential for tackling environmental challenges and sustaining competitive advantage [2,6]. By embedding sustainability into core strategies, ethical leadership contributes to long-term success in an increasingly sustainability-focused market [9,16].

Stakeholder Theory further underscores the strategic importance of ethical leadership. According to this perspective, firms must consider the interests of a wide range of stakeholders—including employees, customers, suppliers, and communities—to ensure long-term viability [22]. Ethical leadership facilitates this by aligning organizational practices with stakeholder expectations, thereby building trust, enhancing reputation, and strengthening stakeholder relationships. This alignment is especially crucial in the context of sustainability, as ethical leaders who prioritize stakeholder well-being are better positioned to balance social, environmental, and financial objectives. Such balance supports a positive organizational image and contributes to sustained performance [4,23].

Signaling Theory also highlights the role of ethical leadership in securing competitive advantage. According to this theory, firms send signals to communicate their intentions and capabilities to stakeholders, thereby reducing information asymmetry [24]. Ethical leadership acts as a credible signal of the firm’s commitment to responsible and sustainable practices. By demonstrating transparency, integrity, and accountability, ethical leaders convey trustworthy information about organizational values and priorities. This signaling builds stakeholder confidence and attracts socially conscious investors, employees, and customers. As a result, ethical leadership not only differentiates the firm but also improves its access to critical resources and opportunities essential for maintaining a competitive edge [25].

In summary, integrating the Resource-Based View, Stakeholder Theory, and Signalling Theory offers a comprehensive framework for understanding the strategic value of ethical leadership in the automotive industry. Ethical leadership serves as a distinctive, hard-to-replicate resource that drives sustainability, strengthens stakeholder relationships, and signals the organization’s commitment to responsible practices. By leveraging these insights, firms can position ethical leadership as a central element of their strategy to achieve long-term competitive advantage and create positive societal impact.

Given these considerations and the RBV framework, it is hypothesized that:

H1a. 

Ethical leadership is positively related to sustainability performance.

2.2. The Direct Relationship Between Ethical Leadership and Financial Performance

The RBV theory further supports the notion that ethical leadership can significantly impact financial performance. Ethical leadership represents a strategic asset that can create value by fostering a positive organizational culture, enhancing employee commitment, and building a strong reputation for integrity and fairness. These elements are crucial for sustaining competitive advantage in the marketplace [16].

Ethical leadership encourages behaviors that improve operational efficiency, reduce turnover, and enhance employee productivity—key factors that contribute to financial performance [11]. Additionally, the trust and loyalty engendered by ethical leadership can attract socially responsible investors and customers, further boosting the firm’s financial outcomes. Recent research has shown that firms with strong ethical leadership tend to achieve higher financial performance, particularly when these leaders emphasize corporate social responsibility (CSR) initiatives [20,26]. The ability of ethical leadership to integrate CSR into the firm’s strategic objectives also aligns with the RBV, as it leverages ethical practices to create long-term value and competitive differentiation [26]. Ethical leadership has become a critical driver of firm performance, especially in terms of sustainability and financial outcomes. In the global automotive industry, where companies face mounting pressure to address environmental and social challenges, ethical leadership is indispensable for navigating these complexities and securing long-term success.

By cultivating a corporate culture grounded in integrity, fairness, and transparency, ethical leadership significantly improves a firm’s sustainability performance. Leaders who model ethical behavior encourage the adoption of sustainable practices such as waste reduction, energy efficiency, and the use of renewable resources [19]. In the automotive sector, where sustainability increasingly serves as a competitive differentiator, these practices are essential to meeting regulatory requirements and stakeholder expectations. Research consistently demonstrates a positive link between ethical leadership and sustainability outcomes. Ethical leaders are more likely to champion initiatives aligned with global environmental standards, strengthening the firm’s reputation and earning stakeholder trust. Furthermore, ethical leadership advances social responsibility by promoting diversity, equity, and inclusion and supporting community development initiatives [9]. Robust governance structures—another hallmark of ethical leadership—reinforce accountability and transparency, both of which are vital for sustaining consumer confidence in the highly scrutinized automotive industry.

The connection between ethical leadership and financial performance is complex and has attracted significant scholarly attention. Although ethical practices often require upfront investments, such as funding sustainable technologies or ensuring fair labor practices, evidence increasingly shows that these investments contribute to long-term financial success [10]. Ethical leadership enhances employee morale and productivity, which are essential for meeting financial objectives [26]. In the automotive sector, ethical leadership is also associated with greater innovation, particularly in developing sustainable products like electric vehicles. These innovations not only help firms comply with environmental regulations but also open new market opportunities that drive revenue growth [3]. Companies guided by ethical leaders tend to cultivate strong relationships with customers and suppliers, boosting brand loyalty and competitive advantage [23]. Moreover, firms that prioritize ethical behavior are more attractive to socially responsible investors, leading to improved access to capital and investment opportunities [9].

Given these arguments and the RBV perspective, it is hypothesized that:

H1b. 

Ethical leadership is positively related to financial performance.

2.3. Moderation Effect of SDG Orientation

The moderating effect of SDG orientation on the relationship between ethical leadership and firm performance is essential for understanding how companies can leverage sustainability commitments to enhance their outcomes. SDG orientation can be defined through three key dimensions—depth, breadth, and concentration—each shaping how effectively ethical leadership translates into superior performance.

Depth of SDG Orientation reflects the extent and detail of SDG-related disclosures. Firms that provide comprehensive sustainability information signal a transparent commitment to specific goals, fostering stakeholder trust. When ethical leadership is paired with in-depth disclosures, it reinforces the firm’s credibility and dedication to addressing critical environmental and social challenges, thereby strengthening stakeholder relationships and boosting investor confidence. This transparency becomes a mechanism that drives improved financial and non-financial results [22]. Consistent with Signaling Theory [24], detailed disclosures reduce information asymmetry by credibly communicating the firm’s values and intentions. By offering thorough SDG information, firms send a strong signal about their commitment to responsible practices, amplifying the positive effects of ethical leadership.

Breadth of SDG Orientation captures the diversity of SDG themes addressed by the firm. A wide-ranging focus across multiple sustainability areas demonstrates a holistic approach to environmental and social responsibility. When combined with ethical leadership, this breadth enhances the firm’s reputation as a proactive, accountable organization. Broad engagement with diverse SDGs increases stakeholder satisfaction, mitigates risks, and generates opportunities for innovation and differentiation, all of which contribute to stronger financial and non-financial performance. Addressing a comprehensive set of sustainability themes enables firms to meet the expectations of varied stakeholder groups, further reinforcing the impact of ethical leadership. This approach aligns with Stakeholder Theory [22], which highlights the importance of considering the interests of all stakeholders to drive long-term success.

Concentration of SDG Orientation reflects how evenly the firm distributes attention and resources across different sustainability priorities. A balanced approach—often measured using the Gini coefficient—demonstrates that firms are committed to addressing multiple critical areas rather than focusing narrowly on a single issue. Ethical leadership that promotes such balance ensures a holistic and resilient sustainability strategy, optimizes resource allocation, and mitigates risks associated with overemphasis. This balance strengthens the firm’s ability to generate sustainable value over time. The Resource-Based View (RBV) theory [16] supports this perspective by suggesting that the effective allocation of resources across strategic initiatives, including sustainability, builds unique capabilities that yield a competitive advantage. By maintaining an even focus on SDGs, firms enhance their resource base and position themselves for sustained success.

In conclusion, the moderating role of SDG orientation—across depth, breadth, and concentration—amplifies the ability of ethical leadership to drive superior firm performance. Organizations that adopt a detailed, comprehensive, and balanced approach to SDG commitments are better positioned to unlock the full potential of ethical leadership. This leads to improved financial results, stronger sustainability outcomes, and enhanced stakeholder relationships. By embedding robust SDG practices into their culture and strategy, firms create an environment in which ethical leadership can effectively deliver long-term value creation and contribute positively to society. Theoretical insights from Signalling Theory, Stakeholder Theory, and the Resource-Based View underscore the strategic importance of SDG orientation in maximizing the benefits of ethical leadership.

We propose a second set of hypotheses to explore the moderating effect of SDG orientation on the relationship between ethical leadership and firm performance:

H2a. 

The tendency of a firm to focus on specific SDG-related themes positively moderates the relationship between ethical leadership and firms’ financial and non-financial performance.

H2b. 

The firm’s tendency to cover a wider variety of SDG-related themes positively moderates the relationship between ethical leadership and firms’ financial and non-financial performance.

H2c. 

The tendency of a firm to balance attention towards different SDGs positively moderates the relationship between ethical leadership and firms’ financial and non-financial performance.

The research design shown in Figure 1 summarizes the new lines developed in this study.

3. Methods

This study employs a quantitative approach using secondary panel data to examine the impact of ethical leadership on sustainability and financial performance, with an emphasis on the moderating role of SDG orientation.

3.1. Data Source and Sampling Technique

The data for this study were gathered from publicly available secondary sources, including annual reports, sustainability reports, and the financial database Refinitiv Eikon. Ethical leadership data was sourced from CSRHub, specifically focusing on the governance pillar. Financial data and sustainability performance metrics were obtained from Refinitiv Eikon, providing comprehensive and standardized information across firms.

The target population for this study consists of automotive firms listed on CSRHub. The study sample comprises only automotive firms, selected based on data availability and relevance to the research objectives. A purposive sampling technique was utilized to ensure that the selected firms provided comprehensive data on ethical leadership, sustainability initiatives, and financial performance. The final sample includes 420 firms, encompassing both multinational corporations and regional players, allowing for variation in sustainability engagement and market positioning. The sample period for this study is from 2015 to 2024. This sampling strategy ensures that the findings are generalizable across different types of automotive firms.

The data collection covered the period from 2014 to 2024, capturing the complete availability of non-financial reports, which first became widely available in 2015. All companies that publish non-financial reports must have produced one for 2024, while there was insufficient data available from 2024 when the research began. Additionally, data related to digital reputation have been available since 2015, making this period optimal for analysis. Data collection followed a structured analysis protocol. First, target firms were identified based on their inclusion in the 2024 CSRHub list, as documented on the official CSRHub website. Non-financial reports were then collected from the financial database Refinitiv Eikon and publicly available online sources, including company websites. These non-financial reports, which are voluntarily disclosed by companies, provide detailed insights into their social and environmental activities and are critical for investigating stakeholder engagement and operationalizing depth, breadth, and concentration concerning SDG-related activities. After filtering, the sample size was reduced from 457 firms to 420 firms, covering the period from 2015 to 2024, resulting in a total of 4200 observations.

The use of these data sources was justified as follows:

CSRHub: The governance pillar data from CSRHub was chosen because it provides a comprehensive assessment of ethical leadership practices, covering aspects such as board structure, executive involvement, and corporate governance practices. CSRHub aggregates ESG data from multiple reputable sources, ensuring a broad and well-rounded perspective on governance. This data is widely recognized and used in academic research to quantify ethical leadership, as it combines information from industry reports, non-governmental organizations (NGOs), and other independent assessments. The use of CSRHub allows for comparability across firms and industries, which enhances the robustness of the data and supports rigorous empirical analysis.

Refinitiv Eikon: Refinitiv Eikon was selected for financial and sustainability performance data due to its reliability and industry-wide use as a trusted source for standardized financial metrics and sustainability indicators. The database offers consistent and comparable data across firms and over time, which is critical for conducting rigorous panel data analysis. Refinitiv Eikon’s standardized metrics ensure that the data is suitable for cross-sectional and longitudinal studies, making it an ideal choice for this research.

Annual and Sustainability Reports: Annual reports and sustainability reports were utilized to gather firm-specific information, allowing for triangulation of data and enhancing the validity of the findings.

To operationalize the study’s moderating variables—depth, breadth, and concentration—content analysis was used to examine the language and terminology describing sustainable development initiatives. Specific keywords from the United Nations definitions of the 17 SDGs and their 169 targets were applied as part of the search strategy. This ensured that the research remained aligned with established sustainability concepts and clearly defined the scope of the analysis.

In accordance with the recommendations by [24], tables and appendices were used to illustrate the relationship between the data and results, thereby enhancing the validity of the content analysis. To ensure transparency, an appendix containing 155 SDG-related terms was provided, illustrating the connection between the underlying concepts and the collected data [19].

Content analysis was performed on the non-financial reports of the firms to identify their orientation towards sustainable development. The increasing use of content analysis in economics research [16] is attributed to its ability to generate replicable and consistent results [19]. MAXQDA 2020 software (Sozialforschung GmbH, 10557 Berlin, Germany) was utilized to manage and analyse the extensive volume of data efficiently. This analysis covered non-financial reports from 2015 to 2024, and the findings were subsequently used to evaluate the effectiveness of non-financial disclosures.

These sources provided detailed information on ethical leadership indicators, sustainability performance, corporate financial performance, and SDG orientation for automotive firms over the period from 2015 to 2024. The use of a multi-year dataset allows for the examination of temporal changes and trends, reducing the risk of biases associated with cross-sectional studies and enhancing the reliability of the findings.

3.2. Measure

3.2.1. Dependent Variable: Firm Performance

Firm performance was assessed using two primary measures: Return on Assets (ROA) and Tobin’s Q. These indicators, as shown in Table 1, were chosen to capture both accounting-based and market-based perspectives on firm performance.

Return on Assets (ROA): ROA was used to measure the operational efficiency of the firm. It is calculated as the ratio of net income to total assets, reflecting how effectively a company is utilizing its assets to generate profit. ROA is widely used in financial research as a reliable indicator of a firm’s profitability and efficiency in managing its resources [5,27]. Tobin’s Q: Tobin’s Q, calculated as the market value of a firm’s assets divided by the replacement cost of those assets, was used to evaluate the market perception of a firm’s value relative to its assets. A higher Tobin’s Q indicates that the market values the firm’s assets highly, which is often linked to intangible assets such as brand reputation, innovation, and management quality [27]. This measure captures investors’ expectations about the firm’s future growth potential. The financial data for ROA and Tobin’s Q were obtained from Refinitiv Eikon to ensure consistency and comparability across the firms included in the study. Both measures provide a comprehensive view of the firm’s performance, encompassing both internal efficiency and external market valuation. By employing these two complementary indicators, the study aims to provide a holistic assessment of how ethical leadership and SDG orientation influence firm performance.

Corporate sustainability performance (CSP) was assessed using two different ratings to represent CSP in our study: ESG (Environmental, Social, and Governance) metrics from Refinitiv Eikon and Bloomberg. ESG scores provide a comprehensive measure of a firm’s sustainability practices across three key areas: environmental impact, social responsibility, and governance quality [28]. Each of these pillars is rated on a scale of 0 to 100, where 0 indicates poor performance and 100 indicates high performance in sustainability-related activities. The ESG data includes metrics such as greenhouse gas emissions, employee welfare, diversity, board structure, and corporate governance practices, providing a holistic view of each firm’s commitment to sustainable development [7]. By utilizing these ratings, the study aims to capture the firm’s overall corporate sustainability performance and assess its relationship with financial outcomes and ethical leadership. The ESG ratings from Refinitiv Eikon and Bloomberg are widely recognized for their reliability and comparability across firms, making them ideal measures for sustainability performance in this research. This dual approach ensures robustness and consistency in measuring CSP, providing a more comprehensive understanding of the firm’s sustainability efforts. By utilizing both ratings, the study aims to mitigate potential biases and validate the findings through cross-verification.

3.2.2. Independent Variable: Ethical Leadership

Ethical leadership was assessed using data from CSRHub, specifically focusing on the governance pillar. Ethical leadership is an intangible asset that reflects a firm’s commitment to responsible management and corporate governance. The governance pillar data includes several indicators, such as the presence of ethical codes of conduct, the establishment of board-level committees focused on ESG (Environmental, Social, and Governance) issues, and the involvement of top management in sustainability initiatives [20,21]. The governance pillar was chosen as it provides a detailed measure of how well the firm’s leadership aligns with ethical standards and sustainability goals. Ethical leadership influences corporate culture, promotes stakeholder trust, and drives engagement in sustainable business practices. This variable was quantified based on ratings provided by CSRHub, which aggregates ESG data from multiple sources to ensure a comprehensive evaluation of each firm’s governance practices. The CSRHub ratings were used as a proxy for ethical leadership, as they reflect the firm’s commitment to integrity, transparency, and accountability in leadership roles [5,9]. CSRHub ratings range from 0 to 100, where 0 indicates low ethical leadership and 100 indicates high ethical leadership. These indicators were coded and quantified based on the CSRHub data, following the guidelines established in prior literature to maintain consistency and reliability.

3.2.3. Moderator Variable: Effectiveness of Non-Financial Information

The measurement of the effectiveness of non-financial information draws upon previous literature, notably the work of [26], who proposed a disclosure depth and breadth index for quantifying integrated reporting in terms of stakeholders. Furthermore, [2,21] conducted an analysis of non-financial disclosure, considering dimensions such as depth, breadth, and concentration.

Table 1. Operational definitions and measurement approaches for the study variables.

Variable	Measurement	Description	Recent Studies
Tobin’s Q	Market value of a firm’s assets divided by the replacement cost of those assets	Evaluate the market perception of a firm’s value relative to its assets	[16,17,21,29]
Return on Equity (ROE)	Percentage (%), net income divided by shareholders’ equity	Financial performance indicator reflecting profitability	[5,16,17,27]
Corporate sustainability performance (CSP)	Two different metrics from Refinitiv Eikon and Bloomberg	Rated from 0 to 100, where 0 indicates poor performance and 100 indicates high performance in sustainability-related activities	[28]
Ethical leadership	Data from CSRHub	Intangible asset that reflects a firm’s commitment to responsible management and corporate governance	[20,21]
Firm Size (FS)	Logarithm of total assets (US$ million)	Controls for resource availability and operational scale	[16,17,21]
Leverage	Net debt divided by total equity	Firm’s financial risk	[17,30]
Return on equity (ROE)	Dividing net income by shareholders’ equity	Firm’s ability to generate profit from its equity base	[31]
Research and Development (R&D) intensity	R&D expenses as a percentage of total sales	Firm’s focus on innovation and long-term growth	[16,17,21,32]
Selling, General, and Administrative (SG&A) expenses	Total of operating costs not directly tied to producing goods or services	Day-to-day operating costs not related to production of goods or services	[17,19]
Free Cash Flow	Cash generated after operating expenses and capital expenditures	Financial Flexibility	[33,34]

Table 1. Operational definitions and measurement approaches for the study variables.

Variable	Measurement	Description	Recent Studies
Tobin’s Q	Market value of a firm’s assets divided by the replacement cost of those assets	Evaluate the market perception of a firm’s value relative to its assets	[16,17,21,29]
Return on Equity (ROE)	Percentage (%), net income divided by shareholders’ equity	Financial performance indicator reflecting profitability	[5,16,17,27]
Corporate sustainability performance (CSP)	Two different metrics from Refinitiv Eikon and Bloomberg	Rated from 0 to 100, where 0 indicates poor performance and 100 indicates high performance in sustainability-related activities	[28]
Ethical leadership	Data from CSRHub	Intangible asset that reflects a firm’s commitment to responsible management and corporate governance	[20,21]
Firm Size (FS)	Logarithm of total assets (US$ million)	Controls for resource availability and operational scale	[16,17,21]
Leverage	Net debt divided by total equity	Firm’s financial risk	[17,30]
Return on equity (ROE)	Dividing net income by shareholders’ equity	Firm’s ability to generate profit from its equity base	[31]
Research and Development (R&D) intensity	R&D expenses as a percentage of total sales	Firm’s focus on innovation and long-term growth	[16,17,21,32]
Selling, General, and Administrative (SG&A) expenses	Total of operating costs not directly tied to producing goods or services	Day-to-day operating costs not related to production of goods or services	[17,19]
Free Cash Flow	Cash generated after operating expenses and capital expenditures	Financial Flexibility	[33,34]

Depth

We revised the measurement of the depth of SDG disclosures to provide a more comprehensive understanding of each firm’s engagement with SDGs. This depth measurement represents the total volume of SDG-related information that is disclosed annually by each firm through its sustainability reports. Specifically, it focuses on capturing the extent to which firms provide detailed insights into their contributions towards each of the SDGs. To operationalize this variable, we calculated the total number of sentences used by each firm (i) in their disclosures related to each SDG category (j) during year (t). By quantifying the number of sentences, we aim to objectively assess the level of detail and commitment each firm has towards the different SDGs. This method allows for a clear comparison across firms, helping to distinguish between those that are merely acknowledging the SDGs and those that are actively providing substantial information about their initiatives and contributions. The resulting measurement reflects the depth and thoroughness of SDG-related reporting, which is crucial for evaluating the effectiveness of corporate sustainability efforts. Mathematically, we applied the following formula to compute the index:

$${\mathrm{D}\mathrm{e}\mathrm{p}\mathrm{t}\mathrm{h}}_{\mathrm{i}\mathrm{t}}={\sum }_{\mathrm{j}=1}^{\mathrm{m}}{\mathrm{S}\mathrm{D}\mathrm{G}}_{\mathrm{j}\mathrm{i}\mathrm{t}}{\displaystyle \frac{\sum _{\mathrm{i}=1}^{\mathrm{n}}{\mathrm{S}\mathrm{D}\mathrm{G}}_{\mathrm{j}\mathrm{i}\mathrm{t}}}{\sum _{\mathrm{j}=\mathrm{i}}^{\mathrm{m}}\sum _{\mathrm{i}}^{\mathrm{n}}{\mathrm{S}\mathrm{D}\mathrm{G}}_{\mathrm{j}\mathrm{i}\mathrm{t}}}}$$

In this equation, SDG_jit represents the count of sentences related to SDG _j issued by firm i in year t. Here, m stands for the total number of SDGs, and n represents the total number of firms included in the sample. Therefore, the depth ranges from 0 to 0.745.

Breadth

Breadth captures the diversity of SDG-related themes that each firm addresses in its non-financial reports. It measures the extent to which a firm covers multiple aspects of the SDGs, indicating how comprehensively a firm addresses different themes within each SDG. To operationalize this variable, we calculated the breadth by dividing the number of SDG-related themes covered by the firm by the total number of possible themes related to that particular SDG. This approach provides a ratio that reflects how extensively a firm engages with the various dimensions of each SDG, helping to determine whether a firm’s sustainability efforts are narrowly focused or more broadly distributed across different areas of sustainable development. This measure is essential for understanding the scope and inclusiveness of the firm’s SDG-related initiatives. Here’s the formula used:

$$\mathrm{B}{\mathrm{r}\mathrm{e}\mathrm{a}\mathrm{t}\mathrm{h}}_{\mathrm{i}\mathrm{t}}={\sum }_{\mathrm{j}=\mathrm{i}}^{\mathrm{m}}[{\displaystyle \frac{\sum _{\mathrm{i}=1}^{\mathrm{n}}{\mathrm{S}\mathrm{D}\mathrm{G}}_{\mathrm{i}\mathrm{j}\mathrm{t}}}{\sum _{\mathrm{i}=1}^{\mathrm{k}}{\mathrm{S}\mathrm{D}\mathrm{G}}_{\mathrm{i}}}}]$$

where $\sum _{\mathrm{i}=1}^{\mathrm{n}}{\mathrm{S}\mathrm{D}\mathrm{G}}_{\mathrm{i}\mathrm{j}\mathrm{t}}$ represents the total number of SDG keywords reported by firm i for each SDG j at time t, and $\sum _{\mathrm{i}=1}^{\mathrm{k}}{\mathrm{S}\mathrm{D}\mathrm{G}}_{\mathrm{i}}$ is the total number of SDG keywords for all SDGs i. Therefore, the breadth index ranges from 0 to 7.812. This formula calculates the breadth index, taking into account the total number of SDG keywords reported by each firm for a specific SDG, as well as the total number of SDG keywords across all SDGs.

Concentration

Concentration measures how a firm’s non-financial disclosures are distributed across different SDG-related themes, providing insight into how evenly or unevenly a firm allocates its attention to various SDGs. This indicator reflects the degree to which a firm balances its focus across all SDGs versus concentrating its efforts on just a few specific areas. To operationalize this variable, we employed the Gini coefficient, as suggested by [34], to quantify the level of equality or inequality in each firm’s emphasis on different SDGs. The Gini coefficient ranges from 0 to 1, where a value of 0 indicates perfect equality—meaning the firm gives equal attention to all SDGs—and a value closer to 1 suggests a high level of inequality, indicating that the firm disproportionately emphasizes certain SDGs over others. This measure helps to determine whether a firm’s sustainability disclosures reflect a broad and balanced approach or a more targeted focus, providing valuable insights into their strategic orientation towards sustainable development. The formula for the Gini coefficient used in our study is as follows:

$${\mathrm{C}\mathrm{o}\mathrm{n}\mathrm{c}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}_{\mathrm{i}\mathrm{t}}=1+{\displaystyle \frac{1}{\mathrm{m}}}-\left({\displaystyle \frac{2}{{\stackrel{⃛}{\mathrm{y}}\mathrm{m}}^2}}\right)({\mathrm{y}}_1{2\mathrm{y}}_2+\cdots +{\mathrm{m}\mathrm{y}}_{\mathrm{m}})$$

In this formula, the expression ${(\mathrm{y}}_1{2\mathrm{y}}_2+\cdots +{\mathrm{m}\mathrm{y}}_{\mathrm{m}})$ represents the sequence of disclosure levels for each SDG, ordered from highest to lowest, for each firm in a given year, denoted as “t.” The variable y represents the overall average effectiveness level for each firm in that same year, and m signifies the total number of SDGs. Consequently, the concentration metric can vary from 0 to 0.886, illustrating how a firm’s non-financial disclosure is distributed among the various SDGs, with higher values indicating a more imbalanced distribution. Therefore, the concentration ranges from 0 to 0.893.

3.2.4. Control Variables

Consistent with prior studies, several control variables were included to account for potential heterogeneity across firms. All control data were collected from Refinitiv Eikon. Firm size was measured as the natural logarithm of total assets, capturing the scale of operations [16,17,21]. Financial pressure was controlled using leverage, calculated as net debt divided by total equity, indicating the firm’s financial risk [17,30]. Profitability was controlled using return on equity (ROE), which reflects the firm’s ability to generate profit from its equity base [31]. Research and Development (R&D) intensity, calculated as R&D expenses as a percentage of total sales, was included to control for the firm’s focus on innovation and long-term growth [32]. Selling, General, and Administrative (SG&A) expenses were included to control for operational costs and managerial efficiency [35], while free cash flow was used to control for the firm’s available cash after operating expenses and capital expenditures, indicating financial flexibility [33]. Lastly, country-specific effects were controlled, but since this dummy variable was not statistically significant, it was excluded from the final analysis to focus on more relevant information. These control variables were incorporated to mitigate biases arising from differences in firm size, financial leverage, profitability, and other operational factors, ensuring a more accurate analysis of the relationships between ethical leadership, SDG orientation, and firm performance. These control variables were incorporated to mitigate biases arising from differences in firm size, financial leverage, profitability, and other operational factors, ensuring a more accurate analysis of the relationships between ethical leadership, SDG orientation, and firm performance.

3.3. Estimation Procedures

This study considers the following dynamic panel data econometric model to examine the impact of ethical leadership and SDG orientation on corporate sustainability and financial performance. The model is estimated using the System Generalized Method of Moments (System GMM) estimator, as proposed by [36,37]. This estimator addresses several potential issues, such as the presence of fixed effects (unobserved firm-specific effects), endogeneity of control variables, and the correlation of the independent variable with past and current realizations of the error term. It also corrects for biases related to omitted variables, heteroskedasticity, and autocorrelation within individuals [38].

Model specification can be represented as follows:

y_it = λy_it−1 + βx_it + θ(x_it⋅m_it) + γz_it + η_i + ϵ_it.

(1)

u_it = η_i + ϵ_it

η_i∼IID (0,σ_η²), ϵ_it∼IID (0,σ_ϵ²), and E[η_iϵ_it] = 0

(2)

For i = 1, …, N and t = 2, …, T

where:

y_it: Dependent variable (firm financial performance—ROA, Tobin’s Q—or corporate sustainability performance—ESG scores).

y_it−1: Lagged dependent variable.

x_it: Independent variable (ethical leadership).

m_it: Moderating variables (SDG orientation—depth, breadth, and concentration).

z_it: Control variables (e.g., firm size, leverage, R&D intensity, SG&A expenses).

η_i: Unobserved firm-specific effects.

ϵ_it: Random disturbance term.

(x_it⋅m_it): Interaction term representing the moderating effect of SDG orientation.

Transformation for First Differences

To eliminate unobserved firm-specific effects, the first-difference transformation is applied:

Δy_it = λΔy_it−1 + βΔx_it + θΔ(x_it⋅m_it) + γΔz_it + Δϵ_it

(3)

Taking first differences introduces a new bias, as the differenced error term may be correlated with the lagged dependent variable.

∆u_it = ∆η_it + ∆ε_it ⇒ u_it − u_it−1 = (η_i − η_i) + (ε_it − ε_it−1) ⇒ ∆u_it = ε_it − ε_it−1

To resolve this issue, Refs. [37,39] proposed the System GMM estimator, which combines two equations: one in first differences, with explanatory variables instrumented by their lagged levels, and one in levels, with variables instrumented by their lagged first differences. This dual-equation approach enhances the efficiency of the estimation. The consistency of the System GMM estimation is ensured by two diagnostic tests: the Sargan test for over-identification, which assesses the validity of the instrument set, and the [36] (AR2) autocorrelation test, which checks for the absence of second-order autocorrelation in the residuals, as proposed by [36,39]. We use the xtabond2 command in Stata 16 [38] to conduct the System GMM estimation.

4. Results and Findings

4.1. Descriptive Statistics and Correlation

The descriptive statistics and correlation matrix in

Table 2. Descriptive Statistics and Correlation Matrix.

Variable	Observation	Mean	SD	Max	Min	ROA	Tobin’s Q	CSP_R	CSP_B	Ethical Leadership	Depth (SDG)	Breadth (SDG)	Concentration (SDG)	Size	Leverage	RD Intensity	SG&A	Free Cash Flow
ROA	4200	5.31	1.523	0.241	9.451	1.000
Tobin’s Q	4200	1.712	0.724	0.013	8.567	0.571 ***	1.000
CSP_R	4200	56.65	15.18	94	13	0.421 ***	0.389 ***	1.000
CSR_B	4200	56.65	15.18	94	13	0.421 ***	0.389 ***	0.121 ***	1.000
Ethical Leadership	4200	45.86	12,34	90	23	−0.284 ***	0.323 ***	0.129 ***	0.129 ***	1.000
Depth (SDG)	4200	0.346	0.125	0.745	0	0.129 ***	0.274 ***	0.074 ***	0.124 ***	0.229 ***	1.000
Breadth (SDG)	4200	0.332	0.214	0.781	0	0.199 ***	0.376 ***	0.647 ***	0.887 ***	0.274 ***	0.721 ***	1.000
Concentration (SDG)	4200	0.168	0.365	0.893	0	−0.213 ***	0.404 ***	0.431 ***	0.571 ***	−0.248 ***	−0.585 ***	0.820 ***	1.000
Size	4200	16.808	1.394	16.808	16.808	0.185 ***	0.094 ***	0.110 ***	0.152 ***	0.031 ***	0.208 ***	0.235 ***	0.186 ***	1.000
Leverage	4200	0.226	16.101	0.226	0.226	0.008 ***	0.015 ***	0.111 ***	0.311 ***	0.010 ***	0.006 ***	0.013 ***	0.019 ***	−0.007 ***	1.000
RD Intensity	4200	0.012	0.042	0.012	0.012	0.365 ***	0.220 ***	0.365 ***	0.675 ***	0.011 ***	0.229 ***	0.246 ***	0.251 ***	0.060 ***	0.002 ***	1.000
SG&A	4200	0.055	0.086	0.055	0.055	0.231 ***	0.145 ***	0.411 ***	0.121 ***	0.065 ***	0.122 ***	0.152 ***	0.178 ***	0.184 ***	−0.011 ***	0.092 ***	1.000
Free Cash Flow	4200	0.375	0.483	0.375	0.375	0.296 ***	0.231 ***	0.365 ***	0.775 ***	0.148 ***	0.172 ***	0.186 ***	0.214 ***	0.278 ***	−0.045 ***	0.197 ***	0.121 ***	1.000

Significance levels: p < 0.01 (***).

reveal key relationships between corporate sustainability performance (CSP), financial metrics, ethical leadership, and SDG initiatives. CSP ratings from Refinitiv and Bloomberg show high consistency (r = 0.123 ***), indicating reliable measurement. Ethical leadership positively correlates with Tobin’s Q (0.321 ***), suggesting it enhances market valuation, while its negative correlation with ROA (−0.283 ***) implies a complex impact on profitability. The breadth of SDG engagement correlates strongly with CSP ratings (CSP_R: 0.648 ***, CSP_B: 0.888 ***), indicating that a broader SDG focus improves sustainability scores. Firm size and R&D intensity positively influence CSP and financial performance, enhancing overall valuation. Notably, depth and concentration of SDG involvement have mixed correlations with financial outcomes, underscoring the nuanced nature of sustainability strategies. The dependent variables are correlated with all variables. The correlation coefficients range between −1 and 1, which is within the acceptable limit for interpreting relationships, indicating that the model’s correlations are valid and reliable. The Variance Inflation Factor (VIF) of 2.45 indicates low multicollinearity, suggesting that the model’s estimates are reliable and variable relationships are interpretable.

4.2. Ethical Leadership and Firm Performance

The results from the baseline model in

Table 3. The Impact of Ethical Leadership on Corporate Financial Performance and Sustainability Performance.

Baseline Model					Model
	Corporate Financial Performance		Corporate Sustainability Performance		Corporate Financial Performance		Corporate Sustainability Performance
Variables	ROA	Tobin’s Q	CSP_R	CSP_B	ROA	Tobin’s Q	CSP_R	CSP_B
ROA(t−1)	0.256 *** (0.045)				0.231 * (0.031)
Tobin’s Q(t−1)		0.191 *** (0.023)				0.554 * (0.062)
CSP_R(t−1)			0.474 *** (0.056)				0.156 *** (0.038)
CSP_B(t−1)				0.305 *** (0.039)				0.121 ** (0.028)
Ethical Leadership					0.296 *** (0.028)	0.455 *** (0.037)	0.363 *** (0.022)	0.522 *** (0.038)
Size	−0.261 *** (0.007)	−0.747 *** (0.0003)	−0.3464 *** (0.009)	−0.9189 *** (0.011)	−0.000161 (0.005)	0.180 * (0.026)	0.398 ** (0.043)	0.271 ** (0.033)
Leverage	0.110 * (0.021)	0.328 *** (0.0037)	0.201 *** (0.009)	0.421 *** (0.011)	0.190 * (0.025)	0.428 (0.041)	0.101 (0.023)	0.0421 * (0.013)
RD Intensity	0.141 * (0.017)	0.213 * (0.023)	0.441 * (0.036)	0.1013 * (0.012)	0.241 * (0.027)	0.4313 * (0.039)	0.541 * (0.046)	0.2513 * (0.028)
SG&A	0.379 * (0.033)	0.257 * (0.021)	0.143 * (0.021)	0.722 *** (0.017)	0.479 * (0.037)	0.307 (0.032)	0.343 * (0.024)	0.222 (0.019)
Free Cash Flow	0.026 *** (0.006)	2.067 *** (0.215)	0.078 * (0.012)	0.395 (0.033)	0.096 * (0.015)	0.187 * (0.027)	0.058 *** (0.008)	0.533 *** (0.041)
Constant	0.356 * (0.045)	2.234 (0.156)	3.155 (0.201)	0.655 (0.071)	0.556 * (0.062)	1.134 (0.102)	0.355 (0.049)	0.655 *** (0.058)
Country	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Year	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Observations	4200	4200	4200	4200	4200	4200	4200	4200
Number of firms	420	420	420	420	420	420	420	420
No of Instruments	67	67	67	67	67	67	67	67
AR(1)	−0.148 (0.038)	−2.25 (0.024)	−2.13 (0.061)	−3.25 (0.005)	−0.118 (0.001)	−3.25 (0.004)	−4.03 (0.044)	−5.85 (0.014)
AR(2)	2.28 (0.321)	0.54 (0.642)	0.011 (0.693)	0.69 (0.451)	4.18 (0.213)	0.74 (0.744)	0.611 (0.713)	0.69 (0.655)
Hansen Test	22.31 (0.358)	12.80 (0.139)	42.65 (0.749)	35.57 (0.345)	2.31 (0.358)	2.80 (0.232)	2.65 (0.846)	6.57 (0.343)
Hansen Different Test	2.01 (0.140)	12.108 (0.313)	20.48 (0.138)	7.39 (0.125)	3.01 (0.140)	9.108 (0.435)	0.48 (0.138)	10.39 (0.422)
Sargan Test	18.5 (0.274)	16.4 (0.341)	30.8 (0.667)	21.1 (0.514)	28.4 (0.242)	22.8 (0.527)	16.6 (0.433)	33.2 (0.645)
Wald Test (χ2)	44.3 (0.000)	34.1 (0.000)	28.8 (0.000)	30.6 (0.000)	53.1 (0.000)	43.5 (0.000)	38.2 (0.000)	37.7 (0.000)

Notes: Sample period: 2013–2019. AR(1) and AR(2) represent the [36] tests for first-order and second-order autocorrelation, respectively. A p-value below 0.05 indicates the presence of autocorrelation in AR(1), while AR(2) should show no significant autocorrelation for the model to be valid. The Hansen Test evaluates the validity of the instruments used in the GMM model. A higher p-value (typically above 0.05) suggests the instruments are valid and not over-identified. The Hansen Different Test compares the instrument subsets used in the model to check for validity. A p-value above 0.05 indicates that the instruments are consistent. The Sargan Test checks the overall validity of the instruments. A p-value higher than 0.05 implies that the instruments are not correlated with the error terms. Wald Test (χ²) tests the joint significance of the coefficients in the model. A p-value of 0.000 suggests strong overall significance of the model. Significance levels: p < 0.1 (*), p < 0.05 (**), p < 0.01 (***).

demonstrate that the selected control variables are the best fit for explaining variations in both financial and sustainability performance. The significance of the lagged dependent variables shows strong persistence in both areas, highlighting that past performance is a reliable predictor of future success. This reinforces the importance of continuity in management practices. Among the control variables, R&D intensity and free cash flow stand out, with their positive effects on both financial and sustainability outcomes underscoring the crucial role of innovation and liquidity in driving long-term competitive advantage. Firm size shows mixed results, positively influencing sustainability performance but negatively impacting financial efficiency, which may point to the operational challenges large firms face. Leverage also significantly improves both financial and sustainability outcomes, suggesting that well-managed debt can be an effective tool for enhancing performance, partly due to external pressure to meet responsible management standards. Overall, the baseline model results, with these control variables, provide the best fit for understanding how firms can improve both financial performance and sustainability through strategic investment in innovation, prudent financial management, and leveraging past successes.

The extended model in Table 3 provides valuable insights into the influence of ethical leadership on both corporate financial performance (CFP) and corporate sustainability performance (CSP), specifically with CSP_R (ESG performance from Eikon) and CSP_B (ESG score from Bloomberg). Ethical leadership shows a significant positive impact on financial metrics such as ROA (β = 0.298, p < 0.01) and Tobin’s Q (β = 0.457, p < 0.01). This suggests that firms led by ethical leaders tend to outperform financially, as these leaders cultivate a culture of trust, transparency, and long-term focus, which enhances both operational efficiency and market confidence. The strong impact on Tobin’s Q highlights how ethical leadership boosts market perceptions, likely due to reduced reputational risks and the alignment of business practices with long-term shareholder value creation.

The influence of ethical leadership on corporate sustainability performance is even more pronounced. The results show that ethical leadership significantly improves both CSP_R (β = 0.364, p < 0.01), representing ESG performance from Eikon, and CSP_B (β = 0.524, p < 0.01), the ESG score from Bloomberg. This highlights that firms with ethical leaders are more likely to implement strong sustainability practices that are reflected in their high ESG ratings across different platforms. The stronger impact on CSP_B suggests that Bloomberg’s ESG ratings, which often emphasize transparency and external reporting, are especially responsive to firms with ethical leadership that promotes responsible governance and sustainability disclosure.

These results demonstrate that ethical leadership is closely tied to how well firms perform on both environmental, social, and governance (ESG) criteria, as captured by external assessments from Eikon and Bloomberg. Given the increasing reliance on ESG ratings by investors, regulators, and consumers to assess corporate responsibility, the positive correlation between ethical leadership and high CSP_R and CSP_B scores underscores the importance of ethical leaders in driving comprehensive sustainability efforts.

In summary, the extended model confirms that ethical leadership significantly enhances both financial and sustainability performance. Ethical leaders not only improve financial outcomes, as seen with the positive effects on ROA and Tobin’s Q, but they also position their firms for long-term success by embedding sustainability into corporate strategy, as reflected in the high CSP_R and CSP_B scores. This dual impact illustrates that ethical leadership is a vital asset for firms seeking to excel in today’s sustainability-driven business environment.

4.3. The Moderating Role of SDG-Related Disclosures

In

Table 4. The Moderating Effect of SDG-Related Disclosures on the Nexus between Ethical Leadership and Corporate Financial Performance and Sustainability Performance.

Model 1					Model 2				Model 3
Variables	ROA	Tobin’s Q	CSP_R	CSP_B	ROA	Tobin’s Q	CSP_R	CSP_B	ROA	Tobin’s Q	CSP_R	CSP_B
ROA(t−1)	0.326 ** (0.049)				0.505 ** (0.051)				0.385 * (0.043)
Tobin’s Q(t−1)		0.301 * (0.039)				0.706 * (0.068)				0.276 *** (0.041)
CSP_R(t−1)			0.624 ** (0.069)				0.651 *** (0.049)				0.211 ** (0.032)
CSP_B(t−1)				0.475 ** (0.053)				0.714 *** (0.060)				0.264 ** (0.053)
Ethical Leadership	0.358 * (0.033)	0.527 ** (0.043)	0.425 * (0.028)	0.594 ** (0.044)	0.548 ** (0.036)	0.747 *** (0.049)	0.491 ** (0.031)	0.701 ** (0.050)	0.582 ** (0.041)	0.828 *** (0.053)	0.454 ** (0.027)	0.723 ** (0.055)
Disclosure Depth	0.361 ** (0.030)	0.185 * (0.019)	0.1264 * (0.016)	0.209 ** (0.027)
Disclosure Breadth					0.416 ** (0.059)	0.251 ** (0.028)	0.514 ** (0.061)	0.395 * (0.046)
Disclosure Concentration									0.351 ** (0.046)	0.205 * (0.034)	0.534 ** (0.042)	0.639 ** (0.048)
Ethical Leadership × Depth	0.334 * (0.025)	0.383 ** (0.034)	0.257 * (0.016)	0.425 ** (0.031)
Ethical Leadership × Breadth					0.276 * (0.020)	0.439 ** (0.035)	0.363 * (0.025)	0.397 ** (0.032)
Ethical Leadership × Concentration									0.427 ** (0.030)	0.548 ** (0.043)	0.384 ** (0.023)	0.563 ** (0.041)
Size	0.096 ** (0.008)	2.237 ** (0.239)	0.148 * (0.015)	0.465 ** (0.038)	0.166 * (0.019)	0.257 ** (0.031)	0.128 * (0.011)	0.096 ** (0.008)	2.237 ** (0.239)	0.148 * (0.015)	0.465 ** (0.038)	0.166 * (0.019)
Leverage	0.260 ** (0.030)	0.498 ** (0.045)	0.171 * (0.027)	0.1121 * (0.017)	0.560 ** (0.040)	0.898 ** (0.060)	0.181 * (0.033)	0.481 ** (0.044)	0.658 ** (0.052)	0.868 ** (0.069)	0.191 * (0.021)	0.491 ** (0.026)
RD Intensity	0.311 * (0.031)	0.5013 ** (0.044)	0.611 ** (0.052)	0.3213 * (0.029)	0.611 ** (0.035)	0.883 ** (0.051)	0.851 ** (0.056)	0.9213 ** (0.058)	0.701 * (0.043)	0.893 ** (0.055)	0.761 ** (0.049)	0.9113 ** (0.061)
SG&A	0.549 ** (0.042)	0.377 ** (0.034)	0.413 * (0.027)	0.292 * (0.022)	0.3279 ** (0.035)	0.777 ** (0.050)	0.663 ** (0.044)	0.512 ** (0.034)	0.5179 ** (0.040)	0.697 ** (0.046)	0.673 ** (0.044)	0.522 ** (0.031)
Free Cash Flow	0.166 * (0.019)	0.257 ** (0.031)	0.128 * (0.011)	0.603 ** (0.046)	0.796 ** (0.064)	0.387 ** (0.040)	0.218 ** (0.026)	0.865 ** (0.068)	0.296 ** (0.023)	0.317 ** (0.034)	0.198 * (0.018)	0.837 ** (0.050)
Constant	0.626 ** (0.075)	1.204 ** (0.118)	0.425 ** (0.056)	0.725 ** (0.067)	0.626 ** (0.051)	0.756 ** (0.059)	3.325 ** (0.194)	0.825 ** (0.090)	0.216 ** (0.046)	3.306 ** (0.234)	0.625 ** (0.081)	0.695 ** (0.060)
Country	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Year	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Observations	4200	4200	4200	4200	4200	4200	4200	4200	4200	4200	4200	4200
Number of firms	420	420	420	420	420	420	420	420	420	420	420	420
No of Instruments	67	67	67	67	67	67	67	67	67	67	67	67
AR(1)	−0.138 (0.004)	−3.55 (0.006)	−4.23 (0.048)	−6.65 (0.016)	−1.178 (0.031)	−4.55 (0.016)	−6.53 (0.062)	−9.15 (0.020)	−1.298 (0.036)	−4.35 (0.020)	−6.93 (0.059)	−9.75 (0.020)
AR(2)	4.38 (0.293)	0.84 (0.814)	0.711 (0.783)	0.79 (0.725)	4.28 (0.493)	1.74 (0.811)	0.261 (0.863)	0.78 (0.515)	4.38 (0.501)	1.84 (0.813)	0.251 (0.861)	0.88 (0.519)
Hansen Test	10.31 (0.438)	10.80 (0.312)	10.65 (0.916)	14.57 (0.423)	50.31 (1.425)	40.80 (0.618)	30.65 (0.864)	24.57 (0.725)	50.51 (1.431)	40.60 (0.622)	30.45 (0.861)	24.77 (0.729)
Hansen Different Test	11.01 (0.220)	17.108 (0.515)	8.48 (0.218)	19.39 (0.502)	30.01 (0.422)	20.108 (0.313)	32.48 (0.707)	25.39 (0.802)	30.21 (0.426)	20.308 (0.316)	32.68 (0.704)	25.49 (0.805)
Sargan Test	36.4 (0.322)	30.8 (0.597)	24.6 (0.503)	41.2 (0.715)	30.7 (0.602)	28.4 (0.469)	34.8 (0.673)	33.2 (0.650)	30.5 (0.605)	28.8 (0.471)	34.5 (0.676)	33.5 (0.652)
Wald Test (χ2)	61.1 (0.000)	51.5 (0.000)	46.2 (0.000)	45.7 (0.000)	67.8 (0.000)	63.2 (0.000)	49.1 (0.000)	55.3 (0.000)	69.3 (0.000)	63.5 (0.000)	50.1 (0.000)	56.3 (0.000)

Notes: Sample period: 2013–2019. AR(1) and AR(2) represent the [36] tests for first-order and second-order autocorrelation, respectively. A p-value below 0.05 indicates the presence of autocorrelation in AR(1), while AR(2) should show no significant autocorrelation for the model to be valid. The Hansen Test evaluates the validity of the instruments used in the GMM model. A higher p-value (typically above 0.05) suggests the instruments are valid and not over-identified. The Hansen Different Test compares the instrument subsets used in the model to check for validity. A p-value above 0.05 indicates that the instruments are consistent. The Sargan Test checks the overall validity of the instruments. A p-value higher than 0.05 implies that the instruments are not correlated with the error terms. The Wald Test (χ²) tests the joint significance of the coefficients in the model. A p-value of 0.000 suggests strong overall significance of the model. Significance levels: p < 0.1 (*), p < 0.05 (**), p < 0.01 (***).

, the interaction terms between ethical leadership and various dimensions of SDG-related disclosures—Depth, Breadth, and Concentration—reveal important insights about how these disclosures moderate the relationship between ethical leadership and corporate performance, both in terms of financial (CFP) and sustainability performance (CSP).

4.3.1. Interaction of Ethical Leadership × Disclosure Depth

The interaction between ethical leadership and disclosure depth significantly enhances both financial and sustainability outcomes. For ROA (β = 0.335, p < 0.05) and Tobin’s Q (β = 0.382, p < 0.01), this interaction suggests that firms that not only have strong ethical leadership but also disclose detailed SDG-related information tend to perform better financially. The enhanced depth of disclosures signals to stakeholders, including investors, that the company is committed to transparency and long-term sustainability, which in turn strengthens market confidence and operational efficiency. Similarly, the significant positive effects on CSP_R (β = 0.257, p < 0.05) and CSP_B (β = 0.424, p < 0.01) show that detailed sustainability disclosures, when paired with ethical leadership, lead to improved sustainability performance across both Eikon and Bloomberg ESG scores.

4.3.2. Interaction of Ethical Leadership × Disclosure Breadth

The interaction between ethical leadership and disclosure breadth also significantly influences both CFP and CSP. For Tobin’s Q (β = 0.439, p < 0.01), the results suggest that firms that disclose information on a wide range of SDG topics, in combination with strong ethical leadership, enjoy better market valuation. Broad disclosures indicate a holistic approach to sustainability, addressing various stakeholder concerns and fostering broader trust. This interaction also significantly impacts sustainability performance, with positive effects on both CSP_R (β = 0.363, p < 0.05 and CSP_B (β = 0.397, p < 0.01), suggesting that addressing a wide array of SDG themes enhances how firms are perceived in terms of their ESG commitments.

4.3.3. Interaction of Ethical Leadership × Disclosure Concentration

The interaction between ethical leadership and disclosure concentration demonstrates strong positive effects on both financial and sustainability outcomes. The significant impact on ROA (β = 0.427, p <0.01) and Tobin’s Q (β = 0.548, p < 0.01) indicates that firms focusing their SDG disclosures on key areas—rather than spreading their efforts thinly—can amplify the benefits of ethical leadership in driving financial performance. Concentrated disclosure efforts likely reflect a strategic focus on high-impact sustainability initiatives, enhancing investor confidence and operational success. Furthermore, this interaction significantly improves sustainability outcomes, with strong positive effects on CSP_R (β = 0.384, p < 0.01) and CSP_B (β = 0.563, p < 0.01). Concentrating disclosures on critical sustainability areas helps these firms achieve higher ESG ratings, as both Eikon and Bloomberg value depth in addressing key sustainability challenges.

The interaction effects in Table 4 highlight the importance of SDG-related disclosures as moderators in the relationship between ethical leadership and corporate performance. Firms that not only exhibit ethical leadership but also enhance the depth, breadth, or concentration of their SDG disclosures experience amplified financial and sustainability benefits. These interactions suggest that ethical leadership is most effective when complemented by clear, focused, and comprehensive SDG disclosures, which help strengthen both market confidence and ESG performance.

5. Discussion

This study investigates how ethical leadership impacts corporate financial performance (CFP) and corporate sustainability performance (CSP), while also examining how a firm’s orientation toward SDG-related disclosures moderates these relationships. The results offer strong empirical support for the proposed hypotheses, showing that ethical leadership is a significant driver of both financial success and sustainability achievements [1,6]. Furthermore, the positive effects of ethical leadership are further enhanced when organizations adopt SDG-related disclosures that are comprehensive in their depth, breadth, and concentration.

The results provide compelling evidence supporting both H1a and H1b. Ethical leadership plays a critical role in strengthening corporate financial performance and sustainability outcomes [5,6]. By fostering a culture of integrity, transparency, and accountability, ethical leaders enhance internal governance and build greater stakeholder trust [4]. This environment contributes to improved operational efficiency, higher profitability, and increased market valuation, confirming H1b, which posits that ethical leadership is positively associated with financial performance [12,20,26].

The positive link between ethical leadership and corporate sustainability performance (CSP)—as measured by ESG performance ratings and behavioral ESG scores—supports H1a, which proposed that ethical leadership is positively related to sustainability outcomes [2,17]. Ethical leaders are more inclined to embed sustainability into core business operations, driving superior ESG performance across environmental, social, and governance dimensions. These findings are consistent with a growing body of evidence showing that organizations committed to responsible leadership are better equipped to meet stakeholder expectations and address global sustainability challenges [4,5].

The moderating role of SDG-related disclosures in the relationship between ethical leadership and performance offers strong empirical support for H3a, H3b, and H3c. The results indicate that firms with more comprehensive SDG disclosures—whether in terms of depth, breadth, or concentration—derive greater benefits from ethical leadership [20]

H3a. 

The depth of SDG-related disclosures positively moderates the relationship between ethical leadership and performance.

Findings affirm H3a, showing that the interaction between ethical leadership and the depth of SDG disclosures significantly improves both financial and sustainability outcomes [20]. Firms that provide detailed, substantive information about their SDG initiatives are perceived as more transparent and authentically committed to sustainability. This depth of disclosure enhances the positive impact of ethical leadership by reinforcing stakeholder trust and market confidence.

H3b. 

The breadth of SDG-related disclosures positively moderates the relationship between ethical leadership and performance.

H3b is supported by evidence showing a significant positive interaction between ethical leadership and the breadth of SDG disclosures [2]. Firms that cover a wide array of SDG themes in their disclosures exhibit a holistic and inclusive approach to sustainability. This broad engagement enables them to connect with a diverse range of stakeholders, thereby strengthening relationships and enhancing both financial and ESG performance [7].

H3c. 

The concentration of SDG-related disclosures positively moderates the relationship between ethical leadership and performance.

The findings also validate H3c, revealing that when ethical leadership is coupled with a concentrated focus on key SDG areas, performance significantly improves [2]. By prioritizing disclosures in areas where they can exert the greatest impact, firms achieve strategic alignment between their sustainability efforts and core business competencies. This targeted approach amplifies the effectiveness of ethical leadership, resulting in superior financial returns and enhanced sustainability outcomes [9]

In conclusion, this study offers robust empirical evidence that ethical leadership, when combined with comprehensive SDG-related disclosures, drives both financial success and sustainability performance [5,9]. The results validate the proposed hypotheses, underscoring that ethical leadership is a vital asset for firms aiming to strengthen corporate performance while advancing global sustainability objectives. Moreover, the moderating role of SDG disclosures highlights the critical importance of transparency and strategic alignment in amplifying the benefits of ethical leadership. Organizations that integrate ethical leadership with clear, focused SDG reporting are better equipped to fulfill stakeholder expectations, achieve long-term financial resilience, and contribute meaningfully to the SDGs [7,40]

6. Conclusions

This study demonstrates the substantial impact of ethical leadership on both corporate financial performance (CFP) and corporate sustainability performance (CSP), highlighting the value of leadership grounded in ethical principles and transparency. The findings show that firms led by ethical leaders consistently outperform their peers in key financial metrics, including Return on Assets (ROA) and Tobin’s Q, while also achieving higher ESG performance [41,42]. These results underscore the essential role of ethical leadership in fostering trust, accountability, and long-term value creation.

In addition, the moderating effect of SDG-related disclosures—across depth, breadth, and concentration—significantly strengthens the positive influence of ethical leadership on financial and sustainability outcomes. Firms that pair ethical leadership with detailed, comprehensive, and balanced SDG disclosures realize even greater benefits, as these practices enhance transparency, deepen stakeholder engagement, and align organizational efforts with global sustainability objectives.

The relationship between ethical leadership and firm performance is complex and often shaped by contextual factors such as industry dynamics, market conditions, and firm-specific characteristics.

One of the central debates focuses on the financial impact of ethical leadership. Some studies contend that the costs associated with ethical practices—such as investing in sustainable technologies, upholding fair labor standards, and ensuring transparency—can reduce short-term profitability. In contrast, other research highlights the long-term financial advantages of ethical leadership, suggesting these investments strengthen brand loyalty, lower regulatory risks, and attract socially responsible investors. This divergence in findings indicates that the financial outcomes of ethical leadership largely depend on how effectively firms integrate ethical practices into their overall strategy and the timeframe used to measure performance.

Similarly, the effect of ethical leadership on sustainability performance varies across different contexts. While ethical leadership is generally linked to better sustainability practices, its impact is shaped by factors such as organizational culture, stakeholder expectations, and the regulatory environment. In highly regulated industries like automotive, ethical leadership often drives substantial improvements in sustainability due to external pressures and heightened public scrutiny. Conversely, in less regulated sectors, its influence may be less pronounced, resulting in more mixed outcomes.

Organizational culture is particularly important in determining how successfully ethical leadership translates into sustainability results. Companies with a strong commitment to sustainability are more likely to see meaningful benefits, as ethical leadership aligns closely with their strategic priorities. In firms where sustainability is not deeply ingrained, however, the positive effects of ethical leadership may be weaker, leading to less significant performance improvements.

Overall, this research contributes to the expanding literature on leadership and sustainability by demonstrating that ethical leadership is not only consistent with moral and social responsibility but also serves as a strategic asset for driving superior financial and sustainability performance in today’s business landscape. Future research could extend the investigation beyond the automotive industry to explore ethical leadership and related themes in other sectors.

6.1. Implications

The findings of this study carry important implications for corporate leaders, policymakers, and investors alike. For corporate leaders, the results emphasize the strategic value of ethical leadership, not only in enhancing financial performance but also in bolstering a firm’s sustainability credentials. Leaders should focus on cultivating an organizational culture grounded in ethical principles, transparency, and long-term value creation. The study shows that ethical leadership is a key driver of both operational efficiency and market confidence, leading to superior outcomes in profitability and ESG performance. Moreover, to maximize the benefits of ethical leadership, firms should integrate SDG-related disclosures into their corporate strategies. The depth, breadth, and concentration of these disclosures provide a clear signal to stakeholders—especially investors, regulators, and customers—that the company is committed to responsible business practices and SDGs. Comprehensive and focused disclosures strengthen the firm’s credibility and stakeholder trust, ultimately contributing to enhanced corporate reputation and long-term competitive advantage.

For policymakers, the study underscores the role of regulatory frameworks in promoting ethical leadership and sustainable business practices. Encouraging or mandating more detailed and transparent SDG-related disclosures could further support firms in aligning their business strategies with the global sustainability agenda. Policies that incentivize ethical leadership and corporate responsibility would not only improve corporate governance but also foster broader societal benefits, including sustainable economic growth and the achievement of the SDGs. Policymakers should consider promoting guidelines and standards that encourage companies to report comprehensively on their sustainability efforts, creating a level playing field and ensuring accountability.

For investors, the findings reveal significant opportunities in firms that embrace ethical leadership and align with the SDGs. Investors increasingly look beyond short-term financial performance, focusing on long-term value creation through responsible corporate governance and sustainability. Ethical leadership, as demonstrated in this study, is a strong predictor of both financial stability and ESG performance, making these firms attractive for socially responsible investments (SRI) and environmental, social, and governance (ESG)-focused portfolios. Investors should prioritize companies that exhibit strong ethical leadership and comprehensive SDG disclosures, as these firms not only mitigate governance and reputational risks but are also better positioned for sustainable growth.

6.2. Limitations and Future Study

While this study offers valuable insights into the relationship between ethical leadership, SDG-related disclosures, and corporate performance, several limitations should be acknowledged. Firstly, the study is confined to the automotive industry, which, although highly relevant due to its significant environmental and social impact, may limit the generalizability of the findings. The dynamics of ethical leadership and SDG-related disclosures might differ in other industries, particularly those with less regulatory pressure or varying stakeholder expectations regarding sustainability. Future research could expand the analysis to sectors such as technology, healthcare, or finance, where the relationship between leadership and sustainability might take different forms.

Secondly, the timeframe of the study, covering the years 2015 to 2024, may not fully capture more recent developments in both ethical leadership practices and sustainability reporting. The increasing prominence of the SDGs post-2020, combined with evolving regulatory frameworks and stakeholder expectations, could alter the dynamics observed in this study. Future studies could benefit from an extended timeframe, incorporating the effects of global events such as the COVID-19 pandemic and the accelerated focus on climate action and corporate responsibility.

Another limitation arises from the measurement of ethical leadership, which is based on governance-related data from CSRHub. While this measure provides a comprehensive overview of ethical practices, it may not fully capture the more nuanced behaviours and interpersonal dynamics that define ethical leadership. Qualitative measures, such as surveys or case studies, could offer richer insights into how ethical leadership manifests within organizations and influences employee and stakeholder behaviour.

Additionally, the study’s geographic focus may limit its applicability to other regions with different cultural, economic, and regulatory environments. Leadership practices and stakeholder expectations around sustainability vary widely across countries, and the regulatory pressures faced by firms in Europe or the United States might differ significantly from those in emerging markets. Future research could extend the geographic scope to explore how ethical leadership interacts with SDG-related disclosures in different contexts, providing a more global perspective on the issues.

Lastly, while the study focuses on ethical leadership, it does not account for other leadership styles that may also impact corporate performance and sustainability outcomes. Leadership approaches such as transformational leadership or servant leadership may also align with sustainability goals and could be explored in future studies. Comparing the effectiveness of various leadership styles in promoting corporate sustainability could offer a deeper understanding of which approaches are most conducive to achieving both financial and sustainability objectives.