1. Introduction
Since the formulation of the Sustainable Development Goals (SDGs) and the increasing global demand to accelerate their achievement, stakeholders have paid greater attention to corporate contributions to sustainable development, thereby encouraging firms to enhance transparency in non-financial reporting (
Zarzycka & Krasodomska, 2022). Non-financial reporting (NFR) serves as a vital communication tool for providing stakeholders with a comprehensive picture of a company’s sustainable development contributions. Various forms of NFR have emerged, such as corporate social responsibility reporting, triple bottom line reporting, sustainability reporting, integrated reporting, and ESG reporting (
Pratama et al., 2019). Despite these variations, the fundamental function of NFR is to provide information regarding a company’s practices and performance related to sustainability factors—namely environmental, social, and governance (
Di Chiacchio et al., 2024). ESG reporting is closely linked to sustainability reporting, as companies disclose ESG-related information to stakeholders through sustainability reports (
Triwacananingrum & Silphianie, 2023).
The importance of consistent and comparable information for stakeholders has stimulated the development of various global ESG reporting frameworks, including the International Sustainability Standards Board (ISSB), Sustainability Accounting Standards Board (SASB), Global Reporting Initiative (GRI), Task Force on Climate-related Financial Disclosures (TCFD), Corporate Sustainability Reporting Directive (CSRD), and the Integrated Reporting (IR) framework. ESG reporting has also become increasingly relevant due to the rise in ESG investing, where investors integrate environmental, social, and governance factors into decision-making processes.
Jaiswal et al. (
2024) show that certain ESG topics attract investor sentiment, while the Principles for Responsible Investment (PRI) highlight that institutions evaluate responsible investment decisions by considering ESG factors. Notably, 87% of investors with assets under management (AUM) of at least USD 250 billion already integrate ESG policies into their decision-making processes (
Sciarelli et al., 2021).
In Southeast Asia, the Global Reporting Initiative (GRI) is the most widely adopted sustainability reporting standard, including in Indonesia, Malaysia, Singapore, the Philippines, and Thailand. Adoption rates vary across countries, with Singapore showing the highest level (98%), followed by the Philippines (90%), Thailand (86%), Malaysia (84%), and Indonesia (80%), all of which reflect relatively high regional uptake of the GRI framework. (
Pizzi et al., 2022). Each of these countries has introduced national regulations to support sustainability reporting, such as OJK Regulation No. 51/POJK.03/2017 in Indonesia, the National Sustainability Reporting Framework (NSFR) in Malaysia, the SEC Memorandum Circular No. 4 Series of 2019 in the Philippines, the SGX Sustainability Reporting Guide in Singapore, and the guidelines issued by the Stock Exchange of Thailand and the Securities and Exchange Commission in Thailand. Despite these frameworks, the quality of ESG information remains diverse across countries, reflecting contextual national factors (
T. H. Nguyen et al., 2025). This heterogeneity has motivated a growing number of studies exploring determinants of ESG reporting in ASEAN, particularly internal corporate governance mechanisms (
Abu Afifa et al., 2025;
Tran et al., 2021;
Jamil et al., 2021).
Corporate governance plays a crucial role in shaping ESG disclosure, with the board of directors serving as one of the most influential internal mechanisms (
Jamil et al., 2021). As part of top management, the board is responsible for decision-making, policy formulation, and oversight of sustainability reporting (
Yadav & Jain, 2023). Board members can influence ESG disclosure through their individual characteristics, such as age, tenure, education, and expertise (
Minh Ha et al., 2021). This study focuses on two board characteristics—board tenure and board-specific skills—that are expected to shape ESG reporting practices. The rationale is that while long-serving directors accumulate valuable organizational knowledge, directors with financial or industry-specific expertise may bring relevant competencies to strengthen ESG transparency (
Walaszczyk & Mazur, 2024;
Gallego-Álvarez & Rodriguez-Dominguez, 2023).
Board tenure has often been associated with directors’ accumulated experience and firm-specific knowledge. Longer tenure may enhance a director’s ability to make informed sustainability-related decisions (
Mai et al., 2023;
Livnat et al., 2021). However, extended tenure may also reduce openness to innovation and limit fresh perspectives, thereby potentially undermining disclosure quality (
Agustia et al., 2022). Research findings remain inconclusive: while
Saha et al. (
2023) report positive associations between tenure and sustainability disclosure,
Ratri et al. (
2021) find that longer CEO tenure reduces CSR disclosure in Indonesia.
In contrast, board-specific skills refer to the presence of directors with industry-related expertise or financial backgrounds. Directors with industry expertise are better positioned to monitor operations and provide relevant insights for ESG disclosure (
Faleye et al., 2018), while directors with financial expertise can enhance transparency and accountability in reporting (
Naheed et al., 2021). Empirical evidence shows that board expertise improves CSR engagement (
Casciello et al., 2024;
Uyar et al., 2025), though contradictory findings also exist (
Aladwey et al., 2022). Despite its importance, studies investigating the relationship between board expertise and ESG reporting in ASEAN remain limited (
Tran et al., 2021).
Against this background, this study aims to examine the effects of board tenure and board-specific skills on ESG reporting among listed firms in Indonesia, Malaysia, Singapore, the Philippines, and Thailand during 2021–2023. By focusing on five ASEAN countries that contribute significantly to regional GDP, the study enriches the literature by addressing two relatively underexplored board characteristics in the ESG disclosure context. In addition, the findings are expected to provide practical implications for multiple stakeholders: companies may optimize board composition to improve ESG transparency, investors can incorporate board expertise into their ESG risk assessments, regulators may strengthen governance frameworks to ensure high-quality reporting, and ESG professionals can gain insights into the competencies required for effective ESG oversight.
Building on these perspectives, this study conceptualizes ESG reporting as a governance mechanism shaped by both internal board dynamics and external institutional pressures. Specifically, it integrates Stakeholder Theory, which emphasizes firms’ accountability to diverse stakeholder interests; Legitimacy Theory, which views disclosure as a strategy to maintain societal approval; Agency Theory, which underscores the monitoring role of boards in mitigating information asymmetry; and Institutional Theory, which explains how national norms and governance environments influence corporate practices. Together, these frameworks provide a multidimensional rationale for examining how board tenure and board-specific skills affect ESG reporting across different ASEAN institutional settings. Boards with longer tenure may enhance continuity and regulatory familiarity, whereas those with greater industry or financial expertise can improve the technical depth of disclosures. Moreover, by incorporating institutional variation across countries, this study acknowledges that the impact of board attributes on ESG transparency is contingent upon the maturity of governance systems and sustainability norms in each national context.
The remainder of this paper is organized as follows.
Section 2 presents the theoretical framework and development of hypotheses, integrating stakeholder, legitimacy, agency, and institutional perspectives.
Section 3 outlines the research methodology, including data sources, sample selection, variable measurement, and model specifications.
Section 4 reports the empirical results, comprising baseline and moderated regressions, along with robustness and sub-sample analyses.
Section 5 provides a comprehensive discussion of the findings in relation to prior studies and theoretical implications.
Section 6 concludes the paper with a summary of contributions, policy implications, limitations, and recommendations for future research.
3. Methods
The population of this study comprises all publicly listed firms in five ASEAN countries—Indonesia, Malaysia, Singapore, the Philippines, and Thailand—during the period 2021–2023. The data collection process followed a multi-step sequence to ensure consistency and reliability. First, the list of all active publicly listed firms for each country was obtained from the Refinitiv Eikon database. Second, firm-level environmental, social, and governance (ESG) data were extracted, including the ESG reporting scope score, which reflects the breadth and transparency of sustainability disclosures. Third, board-level governance information—covering board tenure, board-specific skills, and board size—was retrieved from the same database to ensure alignment of financial and non-financial metrics. Fourth, firm-level characteristics such as total assets (proxy for firm size), return on assets (proxy for profitability) and debt-to-equity (proxy for leverage) and years since incorporation (firm age) were added from the Refinitiv company fundamentals module.
To maintain data completeness and comparability, firms were included only if all key variables were consistently available for the full 2021–2023 period. This purposive selection resulted in a balanced panel dataset. The final sample consists of 609 firms (1827 firm-year observations), distributed as follows: 78 firms from Indonesia, 268 from Malaysia, 73 from Singapore, 36 from the Philippines, and 154 from Thailand. Firms represent a wide range of industries, ensuring that the results reflect the diversity of the ASEAN corporate landscape and are not biased toward a particular sector.
The choice of the 2021–2023 observation period was guided by two considerations. First, these years capture the post-pandemic recovery phase, during which many firms strengthened their ESG initiatives in response to institutional reforms and investor scrutiny (
Cepeda, 2024). Second, the availability and completeness of ESG and board data in Refinitiv Eikon were highest during this period, ensuring the accuracy and comparability of firm-level observations across countries.
Table 1 summarizes the operational definitions of all variables included in the model. Board tenure and board-specific skills represent key governance attributes hypothesized to influence the quality of ESG reporting. Control variables—firm size, board size, firm age, profitability, and leverage—capture firm-level characteristics that may affect disclosure practices. Firm size is included as a control variable because larger firms generally have more complex operations, greater visibility, and stronger pressure from stakeholders to be transparent in their sustainability reporting. Prior studies show that larger firms tend to disclose more comprehensive ESG information due to their wider impact and higher regulatory scrutiny (
Dinh, 2025;
Farisyi, 2023). Board size is also controlled for, as the number of directors influences the diversity of expertise and perspectives available within the boardroom. Larger boards may provide broader knowledge and networks, which can enhance decision-making and monitoring effectiveness, thereby affecting the extent and quality of ESG disclosure (
Erin & Ackers, 2024;
Alta’any et al., 2024). Firm age is used as a control variable because older firms typically have more established organizational routines, stakeholder relationships, and institutional experience. Firms with a longer operational history may have stronger incentives to disclose ESG information to maintain legitimacy and stakeholder trust (
Githaiga & Kosgei, 2023). Profitability is included to capture the influence of firms’ financial performance on their ability and willingness to engage in ESG disclosure. Firms with higher profitability have greater discretionary resources to invest in sustainability initiatives and may strategically communicate their ESG performance to strengthen reputation and legitimacy. Leverage, measured as the ratio of total debt to total equity, represents the firm’s capital structure and external financing dependence. Highly leveraged firms are subject to closer monitoring by creditors and investors, which can encourage more extensive ESG disclosure as a means of signaling stability and reducing information asymmetry. However, excessive leverage may also constrain financial flexibility, limiting firms’ capacity to allocate resources for sustainability activities.
Data for this study are secondary, collected from the Refinitiv Eikon database. Refinitiv provides standardized, comparable data on corporate governance and ESG disclosures across countries, making it a reliable source for cross-country analysis. The database was accessed to extract values for board characteristics, ESG reporting scope, firm size, board size, and firm age during the 2021–2023 period. All firms with available ESG Reporting Scope data were included, regardless of industry classification, as Refinitiv’s methodology already ensures cross-sector comparability by normalizing ESG indicators across economic activities. No additional industry filters were imposed to maintain the representativeness of the ASEAN corporate landscape and to capture the overall level of ESG transparency within the region. Including firms from multiple industries provides a broader and more realistic picture of ESG reporting behavior in ASEAN markets, where sustainability disclosure practices are still emerging and vary widely across sectors. Moreover, potential industry-related heterogeneity was controlled statistically by including firm-level fixed effects in the baseline regression and robustness models, which capture unobserved, time-invariant firm characteristics such as industry affiliation. Therefore, while the sample covers firms from diverse sectors, the model specification mitigates potential bias, ensuring the robustness and generalizability of the findings.
The data analysis in this study consisted of several stages, integrating descriptive, diagnostic, comparative, and inferential procedures. Descriptive and correlation analyses were first employed to summarize variable characteristics and examine associations among key constructs. To compare variations in board and firm characteristics across ASEAN countries, a Kruskal–Wallis test was conducted as a nonparametric alternative to ANOVA. This method was chosen because it does not assume normality or homogeneity of variances and is more robust under cross-country data heterogeneity. Following this, classical assumption tests—covering normality, heteroskedasticity, autocorrelation, and multicollinearity—were applied to verify model validity. All statistical analyses were performed using EViews 13 econometric software, which provides comprehensive support for panel data estimation and diagnostic testing.
Two regression models were estimated to test the proposed hypotheses. The first model (Model 1) tests H
1 and H
2, which examine the direct effects of board tenure and board-specific skills on ESG reporting. Panel data regression was employed since the dataset combines cross-sectional (firms) and time-series (2021–2023) dimensions (
Gujarati & Porter, 2009). To determine the most appropriate panel data estimation technique, three models were initially considered: the Pooled Ordinary Least Squares (OLS) model, the Fixed Effects Model (FEM), and the Random Effects Model (REM). The Pooled Ordinary Least Squares (OLS) model assumes homogeneity across all firms and time periods, treating the dataset as a single combined sample without accounting for unobserved individual effects. In contrast, the Fixed Effects Model (FEM) allows each firm to have its own intercept, thereby controlling for unobserved, time-invariant characteristics that may influence the dependent variable. This makes FEM particularly suitable when firm-specific traits—such as governance culture or reporting policy—are correlated with the explanatory variables. The Random Effects Model (REM), meanwhile, assumes that these individual effects are random and uncorrelated with the regressors, allowing for more efficient estimation when this assumption holds. Model selection was based on standard diagnostic tests. The Chow test was conducted to compare the pooled and fixed effects specifications, the Hausman test was applied to decide between fixed and random effects, and the Breusch–Pagan Lagrange Multiplier (LM) test was used to test the presence of random effects. Three estimation models—common effect, fixed effect, and random effect—were considered, with the final model selection determined using the Chow, Hausman, and Lagrange Multiplier (LM) tests. The baseline regression is expressed as follows:
The second model (Model 2) tests H
3a and H
3b, which predict that the institutional context moderates the relationship between board characteristics (board tenure and board-specific skills) and ESG reporting. This is examined by introducing interaction terms between each board variable and the institutional context, proxied by country dummy variables. The moderating regression model is specified as follows:
where
Y = ESG Reporting Scope
X1 = Board Tenure
X2 = Board Specific Skills
M = Institutional Context
C1 = Firm Size
C2 = Board Size
C3 = Firm Age
C4 = Profitability
C5 = Leverage
α = Intercept/constant
β = Coefficients for independent variables (X)
γ = Coefficients for control variables (C)
θ = Coefficient for the main effect of the institutional context (M)
δ1, δ2 = Coefficients for the moderating (interaction) effects between X1, X2 and M
ε = Error term
In addition, classical assumption tests were applied to ensure the robustness of the regression model. The tests included multicollinearity, heteroskedasticity, normality, and autocorrelation assessments to ensure the robustness of the regression results. Multicollinearity was examined using the Variance Inflation Factor (VIF) to detect potential intercorrelations among independent variables, as high correlations can distort coefficient estimates and reduce the explanatory power of the model (
Sekaran & Bougie, 2021). Heteroskedasticity was tested using the White test to verify whether the variance of residuals remained constant across observations, since unequal variances can lead to inefficient estimators and biased statistical inferences (
Gujarati & Porter, 2009). Normality was assessed using the Jarque–Bera test to determine whether the residuals followed a normal distribution—an important assumption for reliable statistical inference. However, given the large sample size of this study (n = 1827 firm-year observations), the Central Limit Theorem implies that residuals approximate normality even if mild deviations exist (
Gujarati & Porter, 2009). Because the dataset is panel in nature, the presence of serial correlation was also examined using the Serial Correlation Lagrange Multiplier (LM) test to identify potential autocorrelation of error terms across time within the same firm. Detecting and correcting for autocorrelation is crucial, as serial dependence in panel data can result in biased standard errors and misleading statistical inferences (
Gujarati & Porter, 2009). To address any detected violations of classical assumptions—particularly heteroskedasticity and autocorrelation—all regression models were re-estimated using heteroskedasticity- and autocorrelation-consistent (HAC) robust standard errors, specifically employing the White cross-section correction. This approach adjusts the standard errors without affecting coefficient estimates, thereby ensuring valid hypothesis testing and enhancing the robustness and reliability of the empirical results.
To ensure reliability of empirical results, robustness tests complemented the baseline regression analysis, addressing model specification, heteroskedasticity, serial correlation, and cross-country heterogeneity. Four robustness checks were implemented. First, the baseline one-way fixed effects model was compared with a two-way specification including year fixed effects, evaluating whether relationships remain consistent after controlling for unobserved time-specific shocks. Second, to verify robustness, the model was re-estimated with alternative clustering dimensions, applying year-level clustering to assess inference sensitivity, with firm age excluded to avoid collinearity. Third, sub-sample regressions were conducted for each ASEAN country (Indonesia, Malaysia, Singapore, Thailand, and the Philippines) to capture institutional heterogeneity and test whether board characteristics-ESG reporting relationships remain consistent across settings. Finally, to address potential endogeneity concerns, a panel Two-Stage Least Squares (2SLS) regression was employed, using the lagged value of board-specific skills (X2_LAG) as an instrumental variable. This approach corrects for possible reverse causality or omitted-variable bias between board expertise and ESG disclosure quality.
4. Results
4.1. Descriptives
Table 2 presents the descriptive statistics for all variables. Overall, the data show that while ASEAN firms have relatively experienced boards, there is still wide variability in expertise and ESG transparency, reflecting differing institutional maturity within the region.
Board Tenure (X1), shows a mean value of 8.78 years, with a standard deviation of 4.70. The minimum board tenure is 0.50 years, while the maximum reaches 29.40 years. This distribution indicates that, on average, boards in ASEAN companies have a relatively long tenure, but there is substantial heterogeneity across firms, with some boards composed of almost entirely new members and others consisting of highly experienced directors. Board Specific Skills (X2), has a mean of 49.11%, suggesting that approximately half of board members possess such competencies. The wide range from 0% to 100% reflects significant variation, with some firms having boards lacking any specialized expertise, while others are composed entirely of directors with industry or financial backgrounds. Firm Size (C1) records an average of 21.00 with a standard deviation of 188. The minimum and maximum values (16.31 and 21.75, respectively) highlight the diversity of company sizes in the sample, spanning from relatively small firms to very large corporations. Board Size (C2), averages 8.86 with a standard deviation of 2.93. The distribution ranges from 16.31 to 27.05 (likely reflecting log-transformed or scaled values), showing considerable differences in governance structures across firms. Firm Age (C3) has an average of 31.96 years, with values ranging from newly established firms (0 years) to long-standing corporations operating for more than a century (110.36 years). The wide dispersion (standard deviation 18.62) illustrates generational diversity in the sample, with both relatively young and very mature firms represented. Profitability (C4) shows a mean of 1.91 and a large standard deviation of 7.22, ranging from −8.07 to 205.05. The high upper bound indicates the presence of a few highly profitable firms, whereas the negative minimum values reflect firms experiencing losses during the observation period. The wide dispersion highlights differences in operational efficiency and financial performance across ASEAN firms, which may translate into varying capacities to invest in and disclose ESG initiatives. Leverage (C5), records a mean of 0.04 and a standard deviation of 0.08. The minimum and maximum values (−0.56 and 0.80) indicate substantial variation in capital structure across firms, with some companies operating with negative equity or very low debt levels, while others rely more heavily on external financing. The relatively low average leverage suggests that many ASEAN listed firms maintain conservative financing policies, although the wide range points to significant heterogeneity in financial risk exposure and creditor monitoring intensity within the region. ESG Reporting Score (Y), averages 49.89. The standard deviation of 17.59, together with the range between 0.19 and 91.55, indicates notable variation in ESG disclosure practices across ASEAN firms. On average, companies disclose approximately half of the expected ESG-related information, with some firms showing very limited disclosure and others achieving relatively comprehensive reporting.
Table 3 presents the Pearson correlation coefficients for all variables used in this study. The correlations suggest that board expertise and firm characteristics—rather than tenure—are more strongly linked to higher ESG disclosure among ASEAN firms. Board Tenure (X1) shows a positive association with Board Specific Skills (X2), Firm Age (C3), and Profitability (C4), suggesting that boards with longer average service years are often found in older and more profitable firms. Conversely, Board Tenure is negatively correlated with Firm Size (C1), Board Size (C2), Leverage (C5), and the ESG Reporting Score (Y). This implies that firms with larger size, larger boards, higher debt levels, and stronger ESG reporting tend to have relatively newer boards, indicating that board renewal may accompany improvements in disclosure practices. Board Specific Skills (X2) is positively correlated with Board Tenure but negatively associated with Firm Size (C1), Board Size (C2), and the ESG Reporting Score (Y), while its correlations with Firm Age (C3), Profitability (C4), and Leverage (C5) are weak and statistically insignificant. This pattern suggests that boards with a higher proportion of directors possessing industry-specific or financial expertise are more common in smaller firms with fewer board members, and these boards do not necessarily correspond with higher levels of ESG transparency. Firm Size (C1) exhibits the strongest positive correlation with the ESG Reporting Score (Y), confirming that larger firms tend to disclose more ESG information, consistent with stakeholder and legitimacy perspectives. Firm Size is also positively correlated with Board Size (C2), Firm Age (C3), and Profitability (C4), indicating that larger and more mature firms are both more profitable and likely to have larger boards. However, Firm Size shows a negative association with Leverage (C5), implying that bigger firms rely less on debt financing relative to equity. Board Size (C2) is positively correlated with Firm Size (C1) and the ESG Reporting Score (Y), reinforcing that larger companies typically appoint larger boards and engage in more comprehensive ESG reporting. Its associations with other variables are weak, indicating that board size primarily reflects organizational scale rather than other firm or financial attributes. Firm Age (C3) shows positive correlations with Board Tenure (X1) and Firm Size (C1) but negative correlations with Profitability (C4) and Leverage (C5). These relationships indicate that older firms tend to be larger and governed by more experienced boards, but they are generally less profitable and less dependent on debt financing. The modest positive relationship between Firm Age and ESG Reporting Score suggests that organizational maturity is weakly associated with higher ESG disclosure. Profitability (C4), measured as return on assets, exhibits positive correlations with Board Tenure, Firm Size, and ESG Reporting Score, but negative correlations with Firm Age and Leverage. These results imply that more profitable firms tend to be larger, have moderately experienced boards, and demonstrate higher levels of ESG transparency, while older or more indebted firms are less profitable on average. Leverage (C5), measured by the debt-to-equity ratio, is negatively correlated with Profitability, Firm Size, and Board Tenure, suggesting that firms with higher debt levels are generally smaller, less profitable, and governed by boards with shorter tenure. The correlation between Leverage and ESG Reporting Score is weakly positive but insignificant, indicating that financing structure exerts limited direct influence on ESG disclosure behavior. Finally, the ESG Reporting Score (Y) demonstrates its strongest positive correlations with Firm Size (C1) and Board Size (C2), underscoring that larger and more resourceful firms tend to engage in more extensive ESG reporting. The relationships with Firm Age (C3) and Profitability (C4) are positive but modest, while the associations with Board Tenure (X1), Board Specific Skills (X2), and Leverage (C5) are negative. Overall, these results indicate that firm-level characteristics exert a stronger influence on ESG disclosure than individual board attributes or capital structure variables.
The descriptive statistics indicate substantial heterogeneity across ASEAN firms in terms of board characteristics, firm attributes, and ESG reporting. Average board tenure (X1) is relatively long at 8.78 years, but the wide range—from less than one year to almost three decades—suggests significant variation in director experience across companies. Board Specific Skills (X2) average around 49%, meaning that roughly half of board members possess industry or financial expertise, yet some firms still lack such skills entirely. ESG Reporting Score (Y) averages 49, indicating that firms disclose only about half of the expected ESG information, with disclosure ranging from almost negligible to relatively comprehensive. Firm-level controls also vary widely, with firm age spanning from newly established to over a century, firm size ranging from small to very large corporations, and board size differing considerably across companies.
The correlation analysis complements these findings by revealing patterns of association among variables. ESG Reporting Score shows its strongest positive relationship with firm size and board size, underscoring that larger and more resourceful firms tend to provide more extensive ESG disclosures. Firm age also shows a weak but positive correlation, suggesting that organizational maturity may play some role, though not as strongly as size. By contrast, both board tenure and board-specific skills are negatively associated with ESG reporting. These associations indicate that long-serving boards and those dominated by industry or financial experts are not necessarily linked with higher ESG disclosure; instead, they may be related to lower levels of transparency.
4.2. Multiple Regressions
Table 4 presents the results of the classical assumption diagnostics, panel method selection, and the final fixed-effects regression model estimating the influence of board tenure and board-specific skills on ESG reporting, controlling for firm-level characteristics.
The diagnostic results confirm that the model satisfies several key assumptions of multiple regression. The Jarque–Bera test yields a probability value of 0.311 (
p > 0.05), indicating that the residuals are normally distributed and that the model meets the normality assumption, supporting valid hypothesis testing (
Gujarati & Porter, 2009). The Variance Inflation Factor (VIF) values range from 1.047 to 1.298, all well below the threshold of 10, demonstrating that the explanatory and control variables are not affected by multicollinearity (
Sekaran & Bougie, 2021). In contrast, the White test for heteroskedasticity (
p = 0.000 < 0.05) and the Serial Correlation LM test (
p = 0.002 < 0.05) indicate the presence of non-constant residual variance and autocorrelation over time—common issues in corporate panel datasets (
Gujarati & Porter, 2009). To address these violations, the model was re-estimated using heteroskedasticity- and autocorrelation-consistent (HAC) robust standard errors, clustered at the firm level, through the White cross-section (period-cluster) correction. This adjustment ensures that the estimated coefficients remain unbiased and that statistical inferences are valid even in the presence of heteroskedasticity and serial correlation (
Andrews et al., 2006).
Model-selection diagnostics further validate the use of the fixed-effects specification. The Chow test (
p = 0.000) rejects the null hypothesis of a common intercept across firms, while the Hausman test (
p = 0.000) confirms that firm-specific effects are correlated with the explanatory variables, thereby ruling out the random-effects model (
Abadie et al., 2022). Consequently, the fixed-effects estimator with HAC-robust standard errors was chosen as the most appropriate method, as it controls for unobserved firm heterogeneity and produces consistent parameter estimates.
The regression results demonstrate that the model explains approximately 91 percent of the variation in ESG reporting (adjusted R2 = 0.909), indicating a strong explanatory power. The overall model significance is confirmed by the F-statistic = 30.65 (p < 0.01), suggesting that the independent variables jointly exert a statistically significant effect on ESG reporting. Among the explanatory variables, board-specific skills (X2) exhibit a positive and statistically significant relationship with ESG reporting, implying that boards composed of directors with financial or industry expertise enhance the comprehensiveness and quality of sustainability disclosures. Conversely, board tenure (X1) shows a positive but statistically insignificant effect, suggesting that directors’ length of service does not materially influence ESG transparency.
Regarding the control variables, firm age (C3) is positive and significant, indicating that older firms are more likely to provide extensive ESG disclosures, reflecting accumulated experience, institutional maturity, and stakeholder familiarity. Meanwhile, firm size (C1) and board size (C2) are not significant, suggesting that neither organizational scale nor the number of directors has a direct impact on ESG reporting. The remaining financial controls—profitability (C4) and leverage (C5)—are also insignificant, implying that short-term financial conditions exert limited influence on disclosure practices.
Table 5 presents the results of the moderation model, which introduces interaction terms between board tenure (X1) and board-specific skills (X2) with country dummy variables (M1–M4) to examine how institutional contexts across ASEAN-5 economies shape the relationship between board attributes and ESG reporting. The country dummies represent Indonesia (M1), Malaysia (M2), Singapore (M3), and Thailand (M4), with the Philippines serving as the reference category. The Philippines was selected as the baseline for two main reasons. First, it represents a middle institutional context within the ASEAN-5—less mature than Singapore and Malaysia but more developed than Indonesia and Thailand—allowing a balanced comparison of stronger and weaker ESG environments. Second, empirically, the Philippines sample exhibits moderate variance, minimizing collinearity risks that could arise if a country with extreme ESG scores were used as the base category.
Before estimating the model, a series of classical assumption tests were conducted to ensure the validity of the regression analysis. The Jarque–Bera test for normality yielded a probability value of 0.0006 (
p < 0.05), indicating that the residuals deviate from perfect normality. However, given the large sample size (n = 1827), the Central Limit Theorem justifies that parameter estimates remain unbiased and asymptotically normal, making this deviation acceptable for inference (
Gujarati & Porter, 2009). The White test for heteroskedasticity returned
p = 0.0003 (<0.05), suggesting non-constant variance across observations, while the Serial Correlation LM test yielded
p = 0.0000 (<0.05), confirming the presence of autocorrelation in the residuals. These issues are common in large, unbalanced or cross-country panel settings, especially when multiple interaction terms are included (
Gujarati & Porter, 2009). To correct for these violations, the model was re-estimated using heteroskedasticity- and autocorrelation-consistent (HAC) robust standard errors based on the Newey–West covariance estimator, ensuring that statistical inferences remain reliable despite these departures from classical assumptions.
A fixed-effects (FE) specification was initially considered; however, the inclusion of multiple moderating variables (M1–M42) led to a near-singularity problem in the covariance matrix. This issue arises because firm-specific fixed effects are highly collinear with the country dummy variables and their interaction terms, leaving insufficient within-country variation for estimation. Consequently, the fixed-effects model was computationally infeasible. To maintain model stability and preserve interpretive validity of cross-country moderation effects, the study employed pooled ordinary least squares (OLS) estimation with HAC robust standard errors. This specification remains appropriate because the moderating variables represent institutional-level differences across countries, which do not vary meaningfully within firms over the short sample period (2021–2023). Thus, a pooled approach allows for valid cross-country comparisons while ensuring unbiased coefficient estimates (
Gujarati & Porter, 2009).
The model demonstrates an adjusted R2 of 0.099, indicating that approximately 10 percent of the variation in ESG reporting is explained by board characteristics, institutional settings, and their interactions. The overall F-statistic (p < 0.01) confirms that the combined variables significantly contribute to explaining ESG reporting differences across ASEAN firms.
Regarding the main effects, board-specific skills (X2) remain positive and statistically significant (β = 0.181, p = 0.002), reaffirming that directors possessing financial or industry expertise enhance the quality and comprehensiveness of ESG reporting. Board tenure (X1) also shows a positive and significant effect (β = 0.297, p = 0.027), suggesting that longer-serving boards contribute more effectively to ESG disclosure once cross-country contextual factors are considered. This differs from the baseline model, where tenure was insignificant, indicating that its influence becomes evident only when institutional differences are explicitly modeled.
The country dummy coefficients (M1–M4) are all positive and highly significant, indicating that, relative to the Philippines, firms in Indonesia, Malaysia, Singapore, and Thailand generally exhibit higher levels of ESG disclosure—consistent with their more mature institutional frameworks and stronger ESG structures.
Conversely, most interaction terms (M11–M42) are negative and statistically significant, implying that the positive influence of board attributes on ESG reporting is weaker in countries with more established ESG systems. For example, the significant negative coefficients of M21 (−1.237, p < 0.001) and M22 (−0.296, p < 0.001) suggest that in Malaysia, the marginal effect of board-specific skills and board tenure on ESG reporting diminishes compared to the Philippines. Similar negative moderation effects are observed across other countries, reinforcing the interpretation that institutional environments moderate the strength of board-level drivers.
Overall, these findings indicate that while board-specific skills and tenure positively influence ESG disclosure, their impact varies significantly across national contexts. In more mature institutional settings—such as Malaysia and Singapore—ESG disclosure practices are already institutionalized, reducing the incremental role of individual board characteristics. In contrast, in environments like the Philippines, where ESG structures are still consolidating, directors’ expertise and experience appear to play a more decisive role in advancing disclosure transparency.
4.3. Robustness Check
To ensure the validity and reliability of the baseline findings, several robustness checks were conducted. These checks address concerns regarding model specification, error structure, and cross-country heterogeneity in the sample. First, we compared the baseline one-way fixed effects model (firm fixed effects only) with a two-way fixed effects specification that additionally controls for year effects. The inclusion of period fixed effects accounts for common shocks and macroeconomic conditions that may influence ESG reporting across all firms simultaneously. Although two-way fixed effects models with Driscoll–Kraay standard errors were considered, this approach was deemed unsuitable for the present dataset because of the short time dimension (T = 3 years) and large cross-sectional sample (N = 609 firms). The Driscoll–Kraay estimator requires a moderate-to-long time span for reliable covariance estimation. Instead, heteroskedasticity- and autocorrelation-consistent (HAC) robust standard errors were applied, providing consistent inference for short panels while controlling for firm-level clustering and cross-country heterogeneity (
Hoechle, 2007).
The comparison is provided in
Table 6 below:
Table 6 compares the results of the one-way fixed effects model (firm-specific effects only) and the two-way fixed effects model (firm and year effects) to evaluate the robustness of the main findings. The inclusion of year dummies in the two-way model controls for unobserved macroeconomic or time-specific shocks that may simultaneously influence ESG reporting across all firms. Both models were estimated using heteroskedasticity- and autocorrelation-consistent (HAC) robust standard errors to correct for potential violations of classical assumptions. The results indicate that the main conclusions remain stable across model specifications. In both models, board tenure (X1) remains positive but statistically insignificant, confirming that the length of directors’ service does not materially affect ESG disclosure practices. In contrast, board-specific skills (X
2) continue to exhibit a positive and statistically significant relationship with ESG reporting (
p < 0.05 in both models), reaffirming that directors with financial or industry-specific expertise play a crucial role in enhancing the quality and comprehensiveness of ESG disclosures. Among the control variables, firm age (C3) is significant in the one-way fixed effects model (
p = 0.020) but becomes insignificant once year effects are introduced, suggesting that part of the variation previously attributed to firm maturity may instead reflect broader temporal or regulatory trends. Other control variables—firm size (C1), board size (C2), profitability (C4), and leverage (C5)—remain statistically insignificant across both models, indicating that these firm-level characteristics do not exert a consistent direct influence on ESG reporting when unobserved firm heterogeneity is accounted for. The adjusted R2 values are identical (0.909 in both models), and both models yield highly significant F-statistics (
p < 0.01), indicating strong overall explanatory power and confirming that the inclusion of year fixed effects does not substantially alter model fit. This stability demonstrates that the main findings are robust to alternative specifications, supporting the validity of the fixed-effects estimation strategy.
Second, we tested the sensitivity of the inference to different clustering dimensions. While the baseline model employed firm-level clustering to account for heteroskedasticity across firms and within-firm serial correlation, we also re-estimated the model with standard errors clustered at the year level. To implement this specification, firm age was excluded from the regression because it is a time-invariant variable within the short study window (2021–2023). Including firm age alongside year clustering risks collinearity with the year effects, as any variation attributed to firm age would be absorbed by the time dimension. Excluding this variable ensures the stability of the estimation while still allowing for a robust assessment of whether inference is sensitive to the chosen clustering dimension. Importantly, the exclusion of C3 does not alter the substantive interpretation of the results, as the primary variables of interest—board tenure and board specific skills—remain unaffected.
Table 7 presents the results of a robustness test that compares the regression models with and without firm age (C3) as a control variable to evaluate the stability of the main findings. The results show that including firm age (C3) slightly improves model performance, as reflected in a higher adjusted R
2 and a stronger F-statistic, indicating better overall model fit. When firm age is included, it has a positive and statistically significant coefficient, suggesting that older firms tend to provide more comprehensive ESG disclosures, consistent with the argument that organizational longevity enhances stakeholder accountability and reporting maturity. When firm age is excluded, firm size (C1) becomes significant (β = 3.570,
p = 0.030), indicating that part of the size effect may have been previously absorbed by firm age due to their conceptual and empirical overlap. This shift in significance implies that both variables capture related dimensions of firm capacity—larger firms may have greater resources for disclosure, while older firms may have more established governance routines that support transparency. The other control variables—board size (C2), profitability (C4), and leverage (C5)—remain statistically insignificant in both models, showing limited direct influence on ESG reporting. Importantly, the main finding remains robust: board-specific skills (X2) retain a positive and statistically significant effect on ESG reporting across both specifications (
p < 0.05), confirming that directors with financial or industry expertise consistently contribute to more extensive and higher-quality ESG disclosures. In contrast, board tenure (X1) remains statistically insignificant regardless of the model specification, reinforcing the conclusion that tenure alone does not necessarily translate into improved ESG reporting outcomes. Overall, the robustness test confirms that the inclusion or exclusion of firm age does not materially alter the main results. While firm age contributes to explanatory power, the core relationship between board-specific skills and ESG reporting remains stable and significant, underscoring the reliability of the study’s central finding.
Third, to assess the stability of the results across different institutional contexts, we conducted sub-sample regressions by country. This approach allows us to evaluate whether the main findings are driven by specific national settings or are consistent across the ASEAN-5 sample (Indonesia, Malaysia, Singapore, the Philippines, and Thailand).
Table 8 presents the results of sub-sample regressions estimated separately for each ASEAN country—Indonesia, Malaysia, Singapore, Thailand, and the Philippines—to explore cross-country heterogeneity in the determinants of ESG reporting. All models were estimated using either fixed-effects (FE) or random-effects (RE) specifications, as determined by the Chow and Hausman tests, with heteroskedasticity- and autocorrelation-consistent (HAC) robust standard errors applied to ensure reliable inference. The results reveal marked variation across institutional contexts. In Indonesia and Singapore, board-specific skills (X2) exhibit positive and statistically significant effects on ESG reporting (
p < 0.10 and
p < 0.05, respectively). This finding suggests that in these markets, directors with financial or industry expertise play a key role in enhancing ESG transparency. By contrast, the relationship between board-specific skills and ESG reporting is statistically insignificant in Malaysia, Thailand, and the Philippines, implying that in these environments, disclosure quality is driven more by institutional or regulatory mechanisms than by board-level competencies. Firm age (C3) emerges as a significant determinant of ESG reporting in Malaysia, Thailand, and the Philippines (
p < 0.05), indicating that older, more established firms are more likely to disclose ESG information. This pattern aligns with legitimacy theory, as mature firms tend to have longer stakeholder relationships and face stronger external expectations for transparency. Conversely, firm age is not significant in Indonesia or Singapore, where ESG reporting practices may already be standardized among both young and mature firms. Other firm-level variables—including board tenure (X1), firm size (C1), and board size (C2)—are generally insignificant across countries, though firm size approaches significance in Indonesia (
p ≈ 0.07), suggesting that larger Indonesian firms may have more resources or external pressure to report ESG activities. Profitability (C4) and leverage (C5) show no consistent relationship with ESG reporting in any country. Model fit, as reflected by the adjusted R
2, is highest in Malaysia (0.935) and Indonesia (0.933), indicating strong explanatory power of firm-level characteristics in these countries, while Thailand (0.837) and the Philippines (0.850) show relatively weaker model fit. The diagnostic statistics confirm that all models pass basic robustness checks after HAC correction, with VIF values between 1.0 and 2.7, indicating no multicollinearity concerns. Taken together, the results underscore institutional heterogeneity within ASEAN. The influence of board-specific skills on ESG reporting is strongest in countries with relatively advanced governance frameworks and higher stakeholder scrutiny (Singapore, Indonesia), while firm maturity (C3) is more influential in emerging institutional environments (Malaysia, Thailand, Philippines). These findings complement the moderation analysis in
Table 7, which showed that the strength of the board-ESG relationship diminishes in more regulated contexts. Both the moderation and sub-sample results therefore confirm that the effectiveness of board attributes on ESG reporting is institutionally contingent—shaped by the maturity of ESG regulations, enforcement mechanisms, and corporate governance norms across ASEAN economies.
To verify the consistency of the baseline results, a robustness analysis was performed using a Two-Stage Least Squares (2SLS) model with the lagged value of board-specific skills (X2_L
1) as an instrument.
Table 9 demonstrates that the key relationships are stable across specifications. In both models, firm-level controls such as firm size, board size, and profitability exhibit positive and significant associations with ESG reporting. While board tenure becomes significantly negative under the 2SLS model, board-specific skills lose their significance, suggesting that the positive relationship observed in the fixed-effects model may be influenced by reverse causality or omitted factors. Diagnostic tests confirm that the instrument is valid (J = 0.3429,
p = 0.5581) and that endogeneity is not severe. Thus, the baseline fixed-effects estimates are consistent, and the 2SLS results reinforce the robustness and credibility of the empirical findings.
4.4. Kruskal–Wallis Test
Table 10 presents the Kruskal–Wallis results used to test the significance of variations in all the variables studied in different countries. Since the dataset exhibits potential non-normality and unequal variances across countries, the Kruskal–Wallis test was employed as a nonparametric alternative to ANOVA. This approach is more robust under heteroskedastic conditions and does not assume normal distribution, making it suitable for cross-country comparisons in the ASEAN context. The Kruskal–Wallis test results are not intended to test any specific research hypothesis but rather to provide a more detailed descriptive comparison of variable distributions across countries. This descriptive use of the test complements the inferential models by highlighting institutional and structural heterogeneity that underlies the regression outcomes.
All variables show statistically significant differences across countries at the 5% level, as indicated by the p-values (Sig = 0.000). These findings suggest substantial cross-country heterogeneity in board characteristics, firm attributes, and ESG reporting among listed firms in ASEAN.
The average tenure of board members differs significantly across the five countries. Philippine firms report the longest average tenure (10.72 years), indicating boards that are more stable and long-serving, followed by Thailand (9.58 years) and Malaysia (8.80 years). In contrast, Indonesian boards have the shortest average tenure (7.15 years). These differences may reflect variations in corporate governance codes, board refreshment policies, and cultural preferences in leadership continuity. Longer tenure, as observed in the Philippines, may indicate institutional stability but could also raise questions about openness to renewal.
Substantial variation is observed in the proportion of directors with industry-specific or financial expertise. Malaysian firms report the highest proportion of skilled directors (57.72%), followed by the Philippines (50.09%), while Indonesian firms show the lowest level (34.84%). This gap highlights differences in board recruitment practices and the emphasis placed on technical expertise across countries. The high level in Malaysia suggests stronger emphasis on financial and industry knowledge within boards, possibly influenced by regulatory guidance and investor expectations.
The natural logarithm of total assets indicates that firms in Singapore (22.31) and the Philippines (22.90) are on average larger than those in Indonesia (21.75), Malaysia (20.16), and Thailand (20.83). These results align with Singapore’s and the Philippines’ roles as regional hubs with globally integrated financial markets. The significantly smaller average firm size in Malaysia suggests a more domestically focused market with a larger proportion of medium-sized enterprises represented in the dataset.
Thai firms have the largest average boards (11.24 members), followed by the Philippines (10.24). By contrast, Indonesian firms have smaller boards, averaging only 5.96 members. Larger boards in Thailand and the Philippines may reflect governance codes encouraging diversity of expertise and oversight, whereas smaller boards in Indonesia may indicate leaner governance structures with fewer directors.
The average firm age also differs considerably. Philippine firms are the oldest, with an average age of 47.47 years, followed by Indonesia (40.11 years) and Malaysia (32.00 years). In contrast, firms in Thailand (25.39 years) and Singapore (28.94 years) are relatively younger. These differences may reflect the historical trajectories of capital market development and corporate establishment in each country. Older firms in the Philippines and Indonesia may reflect more established family-owned conglomerates, while younger firms in Singapore and Thailand point to dynamic, relatively recent growth phases.
Significant differences are also found in ESG reporting across countries. Thai firms exhibit the highest average ESG Reporting Score (54.21), followed closely by Singapore (52.46), the Philippines (51.89), and Indonesia (51.85). Malaysian firms record the lowest score (45.44). This variation underscores that, despite regional similarities, country-level governance frameworks, market expectations, and regulatory enforcement influence ESG transparency. Thailand’s leading score is consistent with its more advanced sustainability reporting guidelines by the Stock Exchange of Thailand (SET), while Malaysia’s relatively lower score may suggest gaps between strong board expertise and the actual implementation of ESG disclosure.
These results highlight meaningful institutional and structural differences across ASEAN countries. Singapore and Thailand stand out for larger firm size and higher ESG scores, suggesting stronger market discipline and regulatory effectiveness in encouraging disclosure. The Philippines combines long-serving boards and older firms with moderate ESG reporting, raising questions about whether entrenched governance structures support or constrain transparency. Malaysia shows strong board expertise but lower ESG scores, suggesting that technical knowledge on boards does not automatically translate into improved disclosure quality. Indonesia shows younger boards with limited expertise and smaller size, yet its ESG score is comparable to the Philippines, reflecting progress in sustainability reporting despite governance constraints.
5. Discussion
Table 11 summarizes the hypothesis testing outcomes, indicating which relationships are supported by the empirical evidence and how they align with theoretical expectations. First, board tenure does not exhibit a statistically significant association with ESG reporting in the baseline fixed-effects model. This challenges prior evidence that longer tenure supports sustainability disclosure through experience and monitoring continuity (
Saha et al., 2023;
Mai et al., 2023). Our finding is more consistent with work arguing that prolonged service can reduce adaptability and weaken disciplinary pressure (
Ratri et al., 2021;
Ardianto et al., 2024). From an agency perspective, long service may heighten alignment with management, limiting fresh challenge (
Dimes & Molinari, 2023). From stakeholder/legitimacy views, tenure stability alone does not guarantee responsiveness to evolving expectations; renewal mechanisms (e.g., term limits, staggered rotation) may be necessary to sustain disclosure quality (
Setiarini et al., 2023;
Deegan, 2002). The 2SLS robustness further suggests a negative tenure effect once potential endogeneity is addressed, reinforcing the interpretation that tenure does not bolster ESG transparency. However, because the Durbin–Wu–Hausman test fails to reject exogeneity, we treat the IV result as confirmatory, not overturning the baseline inference: tenure is not a reliable driver of disclosure in this setting.
Second, board-specific skills (industry and financial expertise) are positively and significantly associated with ESG reporting in the main fixed-effects model. This aligns with evidence that technically competent boards better recognize material ESG issues, integrate them into strategy, and improve disclosure credibility (
L. T. M. Nguyen & Nguyen, 2023;
Naheed et al., 2021;
Casciello et al., 2024). The result supports stakeholder theory (boards as capability providers to meet multi-stakeholder accountability) and agency theory (expertise reduces information asymmetry and strengthens oversight;
Fuente et al., 2017), while also advancing legitimacy theory (knowledgeable boards produce disclosures that meet societal expectations;
Hörisch et al., 2020). Importantly, the moderation model shows that while the main effects of skills and tenure are positive in pooled inference, many interaction terms with country dummies are negative and significant, indicating that the marginal contribution of board attributes is weaker in countries with more established ESG regimes relative to the Philippines baseline. This institutional contingency is echoed in the sub-sample regressions. At the 5% level, board-specific skills are significant only in Singapore, while they are statistically insignificant in Indonesia, Malaysia, Thailand, and the Philippines. Taken together, the evidence implies that board expertise matters most where institutional scaffolding is strongest (Singapore) or where baseline practices allow room for board-driven differentiation; once coercive/normative pressures standardize disclosure, the incremental role of individual board attributes diminishes. The 2SLS robustness shows skills become statistically insignificant once instrumented, suggesting that any positive association in FE may embed some reverse-causality/omitted-variable content—but because endogeneity is not detected as severe, the baseline FE interpretation (skills help disclosure) remains the primary inference, with causality stated cautiously.
Third, firm-level controls reveal complementary mechanisms. In the main FE model, firm age is positive and significant, consistent with legitimacy and organizational maturity arguments (
Drempetić et al., 2020;
Khan et al., 2020;
Musa et al., 2025). When year effects are added, age loses significance, indicating that part of its variance is absorbed by common time shocks—suggesting that maturity and period forces are intertwined in the short 2021–2023 window. The with/without C3 check shows that excluding age shifts significance to firm size, implying overlapping explanatory content (visibility, resources vs. accumulated routines). In country sub-samples, age is significant in Malaysia, Thailand, and the Philippines, but not in Indonesia or Singapore, reinforcing the notion that organizational maturity is more salient where institutional frameworks are consolidating. Other controls are largely insignificant across specifications, with the exception that profitability and size emerge as positive and significant in the IV model, consistent with slack-resource and visibility logics. We interpret these as supportive robustness signals rather than contradictions, since the J-statistics test indicates that the baseline FE remains consistent; the IV patterns suggest plausible latent channels once endogeneity is explicitly probed.
Fourth, institutional heterogeneity across ASEAN is substantive. The Kruskal–Wallis tests confirm systematic cross-country differences in board attributes, firm characteristics, and ESG scores, underscoring that disclosure practices are embedded in country-level governance and market structures. Thailand and Singapore display higher average ESG scores, while Malaysia combines high board expertise with lower ESG scoring, pointing to a gap between competence and implementation. The Philippines couples older, longer-tenured boards with mid-range ESG performance, while Indonesia shows shorter tenure and lower board expertise but comparable average ESG scores. These patterns support an institutional-contingency reading: coercive and normative pressures in stronger regimes standardize ESG reporting; in less mature contexts, board capabilities substitute for incomplete external scaffolding (
Ortas et al., 2018;
Pinheiro et al., 2023).
Overall, our evidence suggests that stakeholder and legitimacy theories best explain ESG reporting behavior in ASEAN, with institutional theory clarifying why the governance–disclosure link varies by country. Agency theory remains relevant—especially regarding the non-beneficial or negative role of long tenure—but it appears secondary where capability and institutional maturity jointly shape disclosure. We propose a capability–institutional alignment view: ESG reporting quality depends on the interaction between board competencies and institutional maturity. Where the latter is strong, marginal board effects attenuate; where it is weaker, board expertise becomes pivotal (
Dwivedi et al., 2021;
Tran et al., 2021;
Abu Afifa et al., 2025).
Several policy considerations arise in this context. Firstly, regulatory bodies should prioritize governance that highlights competence, ensuring directors possess at least a basic grasp of ESG, along with industry and financial expertise, while also establishing clear and enforceable disclosure rules (
Padilla-Rivera et al., 2024). Secondly, companies should treat ESG reporting as a process rich in knowledge and strategically connected, rather than merely a compliance requirement (
Işık et al., 2024), with regular updates to the board to prevent stagnation. Investors may assess the board’s expertise and its alignment with local institutional contexts as a measure of the credibility of disclosures.
6. Conclusions
This study examines how board tenure and board-specific skills affect ESG reporting among firms in five ASEAN countries—Indonesia, Malaysia, Singapore, Thailand, and the Philippines—during 2021–2023. The results show board tenure is not significantly associated with ESG reporting, while board-specific skills have a strong positive effect. These results are robust across alternative model specifications, with an adjusted R2 of 0.91 confirming governance attributes’ explanatory power. The first key finding reveals tenure-based experience does not enhance ESG transparency, with board tenure showing positive but insignificant results (p > 0.05). This suggests long-serving directors may not adapt effectively to evolving sustainability frameworks. The second finding shows board-specific skills, particularly financial and industry expertise, significantly determine ESG reporting (p < 0.05). Firms with directors possessing relevant expertise demonstrate stronger ESG reporting, indicating technical competence drives disclosure quality in emerging markets. Institutional context significantly influences the relationship between board attributes and ESG disclosure. In developed environments like Singapore and Malaysia, board expertise’s impact diminishes, while in emerging contexts like Indonesia and Philippines, it plays a crucial role in enhancing transparency. Firm age and size positively correlate with ESG reporting, as organizational maturity increases disclosure incentives. These findings support stakeholder and legitimacy theories, showing ESG reporting is driven by stakeholder demands rather than agency-based monitoring. The results highlight that knowledge-based capabilities promote effective disclosure, while institutional environments shape how board characteristics influence ESG outcomes.
The study thus contributes theoretically by proposing a capability–institutional alignment framework: the effectiveness of corporate governance in promoting ESG transparency depends on the alignment between internal board capabilities and the maturity of external institutional systems. This framework extends prior governance research by demonstrating that, in emerging markets, board competence compensates for institutional weaknesses in regulatory enforcement and reporting infrastructure.
Practically, these findings suggest that regulators in ASEAN should strengthen competence-based governance codes, emphasizing sustainability literacy, financial acumen, and industry knowledge among directors. Firms should adopt targeted board recruitment strategies to ensure a balance of technical expertise and strategic vision. Investors and analysts, in turn, should view the composition of boards—particularly the presence of ESG-skilled directors—as a reliable signal of disclosure quality and sustainability orientation.
While the study provides strong empirical evidence, several limitations must be acknowledged. First, the use of secondary ESG data from Refinitiv, while offering standardized and comparable coverage across firms, may not fully capture the qualitative and contextual dimensions of sustainability disclosure, such as narrative depth or stakeholder engagement tone. Future studies could combine quantitative ESG data with textual or content analysis of sustainability reports to enrich the interpretive dimension. Second, the sample covers five ASEAN countries over a three-year window, which, although regionally representative, limits the ability to capture long-term dynamics. Extending the temporal scope and incorporating additional emerging and developed economies would allow for the exploration of temporal causality and institutional convergence. Third, the study focuses primarily on board tenure and board-specific skills; incorporating additional governance variables—such as board independence, gender diversity, and the presence of sustainability committees—could offer a more holistic view of board effectiveness in ESG oversight.
From a methodological perspective, future research could apply longitudinal or dynamic panel estimators (e.g., GMM or system-GMM) once longer datasets become available to better address endogeneity and causal inference. Cross-level modeling or multi-group SEM could also be used to explicitly test how institutional pressures moderate board–ESG linkages across countries. Theoretically, integrating dynamic capability and resource-based perspectives with stakeholder and legitimacy frameworks could further clarify how board competencies evolve as strategic resources that shape ESG disclosure quality. These extensions would help bridge micro-level governance mechanisms with macro-institutional dynamics, advancing the theoretical depth and empirical precision of corporate sustainability research.