American Journal of Economic and Management Business e-ISSN: 2835-5199 Vol. 4 No. 10 October 2025 1790 Unveiling the Drivers of SDGS 8 Disclosure: Evidence from Governance, Firm Characteristics, and Strategic Factors in Indonesian Listed Firms Nunik Nurnaningsih, Majidah Majidah Telkom University, Indonesia Email: nuniknurnaningsih@student.telkomuniversity.ac.id, majidah@telkomuniversity.ac.id Abstract The issue of decent work (SDG 8), encompassing fair wages, safe conditions, social protection, and workers’ rights, has gained increasing importance in corporate sustainability reporting as expectations for transparency and accountability rise. This study investigates the internal factors influencing Decent Work Disclosure (DWD) among non-financial companies listed on the Indonesia Stock Exchange (IDX) from 2019 to 2023. The analysis examines three key categories: governance mechanisms, firm characteristics, and strategic factors. Variables assessed include corporate governance, gender diversity, firm size, profitability, leverage, asset growth, and cost leadership strategy. Using purposive sampling, 28 companies were selected, producing 140 firm-year observations. Panel data regression was conducted with Stata version 18. The findings reveal that corporate governance negatively affects DWD, whereas firm size, leverage, and cost leadership strategy exert positive effects. Conversely, gender diversity, profitability, and asset growth show limited influence. These results highlight that structural and strategic dynamics are more significant drivers of DWD than formal governance practices, challenging conventional theoretical assumptions. This research contributes to the literature on labor-related sustainability disclosures in emerging markets, offering insights for firms and policymakers aiming to strengthen SDG 8 transparency. Future studies could expand by including moderating factors such as company age or ownership structure to capture more nuanced dynamics in corporate sustainability behavior. Keywords: Sustainable Development Goals (SDG 8); Decent Work Disclosure; Corporate Governance; Firm Characteristics; Strategic Factors; Panel Data Regression; Indonesia. INTRODUCTION Decent work is a fundamental human right and an important foundation for achieving inclusive and sustainable economic growth. The Sustainable Development Goals (SDGs), particularly SDG 8, not only emphasize job creation but also uphold the protection, safety, and dignity of workers (Kreinin & Aigner, 2022). In a global landscape increasingly demanding social responsibility, the issue of decent work has become a key indicator of corporate sustainability across various industrial sectors. However, in practice, industrial transformation and business efficiency pressures often diminish attention to the principles of decent work. Amid increasing labor flexibility, new vulnerabilities have emerged, ranging from income uncertainty, limited access to social security, to low worker bargaining power (Rai et al., 2019; Mațcu-Zaharia et al., 2024). These disparities pose serious challenges, especially in developing countries undergoing rapid industrialization, including Indonesia. Over the past five years, the non-financial sector listed on the Indonesia Stock Exchange (IDX) has experienced rapid growth, from 562 companies in 2019 to 802 in 2023. Unveiling the Drivers of SDGS 8 Disclosure: Evidence from Governance, Firm Characteristics, and Strategic Factors in Indonesian Listed Firms 1791 Unfortunately, the increase in the number of issuers has not been accompanied by improvements in the quality of employment. According to a report by BPJS Ketenagakerjaan (2023), the proportion of workers with contract status (PKWT) continues to increase, while permanent workers (PKWTT) tend to decrease. This situation is further complicated by the implementation of the Job Creation Law No. 11 of 2020, which is seen as making it easier to implement flexible employment practices, including the expansion of outsourcing schemes and short-term contracts, which could weaken the protection of workers' rights (Rizal Jawahir & Nugroho Rizal, 2021; Oktaviani et al., 2024). Attention to this issue has increased with the emergence of a number of actual cases that demonstrate weak labor protection. One such case is that of PT Sri Rejeki Isman Tbk (SRIL), which laid off thousands of workers in the midst of a debt repayment deferral process (Ramli & Setiawan, 2025). On the other hand, workers at PT SAI Apparel Industries in the garment sector reported that they had not been paid overtime wages for months (Sari, 2023). This phenomenon highlights the weakness of protection for workers' basic rights, even in publicly traded companies under public scrutiny. This underscores the need to evaluate the extent to which non-financial companies are committed to achieving decent work sustainably, as well as the importance of strengthening transparency and social responsibility in supporting the achievement of SDG 8. In this context, corporate reporting becomes an important tool that can reflect such commitments in a tangible and measurable way. Therefore, the relevance and quality of reporting are key considerations in promoting more responsible sustainable practices. As global pressure on sustainability practices increases, reporting that includes social dimensions is now an important element of corporate accountability. One manifestation of this commitment is the disclosure of decent work in annual reports and sustainability reports. This information not only reflects compliance with international regulations and standards, but also serves as a means of building public trust and social legitimacy (Hörisch et al., 2020; Suchman, 1995). However, empirical evidence shows that the level of disclosure of decent work aspects is still relatively low, especially in developing countries. Companies tend to focus more on environmental and governance issues, while social aspects such as worker protection are often neglected (Maji, 2022; Gutiérrez-Ponce & Wibowo, 2023). Yet, transparent disclosure of working conditions is highly relevant for informing stakeholders, including investors who are increasingly considering social indicators in their investment decisions (Diener & Habisch, 2021; Saha et al., 2023). Several studies have identified that internal company characteristics can influence their tendency to disclose information about decent work. These include corporate governance factors (Ludwig & Sassen, 2022; Arayssi et al., 2020), gender diversity on the board of directors (Monteiro et al., 2022; Zampone et al., 2024), company size (Bose et al., 2024), profitability (Purbawangsa et al., 2020), leverage (Dhingra et al., 2022), asset growth (Wahyuningrum et al., 2022), and cost leadership strategies (Kharub et al., 2019). However, findings across studies remain inconsistent, creating gaps that require further investigation, particularly in the Indonesian context (United Nations, 2015). By examining the influence of various internal company characteristics on decent work disclosure, this study aims to provide empirical contributions to the literature on social reporting American Journal of Economic and Management Business Vol. 4 No. 10 October 2025 1792 in developing countries. Additionally, this study offers practical implications for policymakers and market actors in promoting more equitable and accountable sustainability reporting practices, in line with SDG 8 targets. Referring to the research problem and inconsistency of research results, the motivation for this study is to examine the factors that are thought to influence SDG8 decent work in non-financial companies listed on the Indonesia Stock Exchange during the period 2019- 2023. Therefore, this study aims to analyze the influence of corporate governance factors, company characteristics, and strategic factors on the disclosure of decent work (DWD) in non-financial companies listed on the Indonesia Stock Exchange for the 2019–2023 period. By identifying the key determinants that drive transparency of SDG 8, the results of this study are expected to make an empirical contribution to the social accounting and sustainable governance literature, especially in the context of emerging markets such as Indonesia. Practically, the research findings can serve as a reference for regulators in developing more effective sustainable reporting policies, as well as for companies to improve social disclosure strategies to build stakeholder legitimacy and trust. METHOD This study employed a quantitative approach with an explanatory research design to test the influence of independent variables on Decent Work Disclosure (DWD). A total of 28 companies, representing approximately 3.5% of the total population, were selected as research samples based on specific criteria during the period from 2019 to 2023. These criteria included continuous listing status on the IDX, availability of annual and sustainability reports, and the presence of at least one female member on the board of directors. The research focused on SDG 8: Decent Work and Economic Growth, analyzing reporting practices related to five specific targets. Each annual and sustainability report was evaluated using content analysis based on business reporting themes from the Global Reporting Initiative and the UN Global Compact, assessing the nature, scope, and quality of reporting. The assessment of independent variables included corporate governance, gender diversity, firm size, profitability, and asset growth, emphasizing the principles of transparency, accountability, responsibility, fairness, and independence. These indicators were intended to foster a fair and ethical work environment while encouraging companies to uphold workers’ rights. RESULT AND DISCUSSION Table 1. Descriptive Statistics Summarze DWD_SDGs8 CG CD FSIZE PROFIT LEV AGW CLS Variable Obs Mean Std. dev. Min Max DWD_SDGs8 140 0.7793571 0.1633164 0.2 1 CG 140 0.9685714 0.0465898 0.9 1 GD 140 0.2823878 0.1685063 0.0666667 0.8 FSIZE 140 30.10263 1.623991 27.52684 33.73062 PROFIT 140 0.0756776 0.099438 -0.4014246 0.4163203 LEV 140 1.297641 2.335073 0.0126784 24.84892 AGW 140 0.0470731 0.1762438 -0.487067 1.4833 CLS 140 0.7318973 0.4480506 0.0063753 2.317043 Unveiling the Drivers of SDGS 8 Disclosure: Evidence from Governance, Firm Characteristics, and Strategic Factors in Indonesian Listed Firms 1793 Table 1 descriptive statistical analysis in this study aims to provide an overview of the data characteristics of each variable used, both dependent and independent variables. Data was taken from 28 non-financial sector companies listed on the Indonesia Stock Exchange (IDX) during the 2019- 2023 period with a total of 140 observations. The following is a systematic explanation of each variable: Decent Work Disclosure (DWD_SDGS8) The main variable that is the focus of this study is the disclosure of decent work based on SDGs 8 indicators. The average disclosure value is 0.7794 or equivalent to 77.94%, with a standard deviation of 0.1633. The minimum and maximum values are 0.2 and 1 respectively, indicating a fairly wide range of disclosure between companies. The relatively low standard deviation indicates consistency in reporting, reflecting that most companies have actively disclosed important aspects of decent work, such as minimum wage, work safety, gender equality, HR development, and protection of labor rights. This disclosure is an important indicator in assessing a company's commitment to sustainability and social responsibility. Corporate Governance (CG) The average corporate governance score is 0.9686 with a very small standard deviation of 0.0465, and a range of values between 0.9 and 1. This indicates that most companies have consistently applied the principles of good corporate governance. These high scores reflect compliance with the principles of transparency, accountability, responsibility, independence and fairness. Good corporate governance practices are an important foundation in supporting sustainability reporting, including the disclosure of aspects of SDGs 8. Gender Diversity (GD) Gender Diversity reflects the proportion of female representation on the board of directors. The average value of gender diversity is 0.2824, with a standard deviation of 0.1685. The minimum value of 0.06 and the maximum of 0.8 indicate a significant disparity between companies. The low average representation of women is a reflection of structural challenges in achieving gender inclusion at the strategic decision-making level. In the context of SDGs 8, gender diversity at the managerial level is an important indicator in promoting a fair and equal work environment. Company Size (FSize) Company size, as measured by the natural logarithm of total assets, shows a mean value of 30.10 with a standard deviation of 1.43. The range of values from 27.52 to 33.73 indicates that the sample is dominated by large-sized companies. Large-scale companies generally have more resources to American Journal of Economic and Management Business Vol. 4 No. 10 October 2025 1794 implement sustainability practices, including the provision of decent work and labor protection, in line with the mandate of SDGs 8. Profitability Company profitability, as measured by Return on Assets (ROA), shows an average value of 0.0757 with a standard deviation of 0.0994. The range of values ranges from -0.4014 (loss) to 0.4163 (high profit). This suggests there is significant variation in the financial performance of companies. Companies with high profitability tend to have more ability to allocate resources to support social and employment programs, while companies with low profitability face limitations in reporting and implementing sustainability programs. Leverage (LEV) Leverage as measured by the debt-to-equity ratio shows an average value of 1.2976 and a standard deviation of 2.3351, with a minimum value of 0.0127 and a maximum of 24.8489. This highly variable value indicates that some companies have a high dependence on debt-based funding. High leverage can inhibit companies from running or reporting proper employment programs as management's main focus is shifted to maintaining liquidity and solvency. Asset Growth (GRW) Asset growth shows an average value of 0.0471 (4.71%) with a standard deviation of 0.1762. The range of values from -0.4871 to 1.4833 shows that some companies experience asset contraction, while others show very high expansion. Asset growth is an important indicator of a company's capacity for labor expansion, facility development, and innovation in HR management. Cost Leadership Strategy (CLS) The cost leadership strategy variable has an average of 0.7313 with a standard deviation of 0.4485, a minimum value of 0.0064 and a maximum of 2.3106. This high variation indicates that not all companies prioritize cost efficiency as the main strategy. Companies with high levels of cost efficiency have greater opportunities to allocate resources into social programs, including workforce training and improving employee welfare, which is in line with the decent work dimension in SDG 8. Selection of the Best Model Three tests were conducted to determine the most appropriate model (common effect, fixed effect, or random effect): (1) the Chow test, (2) the Hausman test, and (3) the Lagrange Multiplier (LM) test. Table 2. Chow Test Model Selection rho 0.80059635 (fraction of variance due to u_i) F test that all u_i = 0 : F (27, 105) = 3.89 Prob > F = 0.0000 Based on the Chow test (F-test) results as shown in the output F(27,105) = 3.89 with a p- value of 0.0000 (<0.05), the null hypothesis (H₀) stating that the Common Effect model is more Unveiling the Drivers of SDGS 8 Disclosure: Evidence from Governance, Firm Characteristics, and Strategic Factors in Indonesian Listed Firms 1795 appropriate is rejected. This means that there are significant differences in individual effects between companies in the sample, so that the Fixed Effect model is stated to be more appropriate to use than the Common Effect. In addition, the rho value of 0.8006 indicates that 80.06% of the total variability in the model is due to heterogeneity between entities (companies). This further strengthens the preference for using the Fixed Effect model due to the influence of unobservable but significant fixed characteristics of the company on the model. Table 3. Breusch-Pagan Lagrange Multiplier Test Model Selection Breusch and Pagan Lagrangian multiplier test for random effect DWD_SDGs8 [NO, t] = Xb + + u [NO, t] Estimated result Var SD = sqrt(Var) DWD_SDGs8 0.0266722 0.1633164 e 0.0122258 0.1105705 u 0.0069979 0.0836532 Test: Var (u) = 0 chibar2(01) = 23.06 Prob > chibar2= 0.0000 Based on the Breusch-Pagan Lagrangian Multiplier test (LM test) results, the chi-bar² value is 23.06 with a probability value (p-value) of 0.0000. 0.05, there is no significant difference between the Fixed Effect and Random Effect model coefficients, so the null hypothesis (H₀) is not rejected. This means that the Random Effect model is more appropriate to use in this study because it is considered to provide efficient and consistent estimates. Although there is a note that the covariance matrix is not positive definite, it does not affect the validity of the test results because the p value obtained remains reliable. Therefore, the Random Effect model was chosen for further panel data regression analysis. American Journal of Economic and Management Business Vol. 4 No. 10 October 2025 1796 Based on the results of the Chow, LM, and Hausman tests, the panel regression model used is Random Effect, because this model produces more stable estimates and has higher estimation accuracy than other models. However, the classical assumption test results show that the initial model has heteroscedasticity and autocorrelation violations, which can cause the estimation to be inefficient. To overcome this, the Panel-Corrected Standard Errors (PCSE) method is used, which is able to correct the estimated standard errors without changing the model structure. This PCSE approach ensures that the resulting estimates remain valid, reliable and robust, despite the violation of classical assumptions in panel data. Table 5. PCSE Model Variable pooled fixed random gee gls_lag pcse rasiocg -0.49439196 -0.4301534 -0.20778966 -0.20851653 -0.27482601 -0.49439196** rasiogendev -0.12905239 0.1749578 -0.01952625 -0.01983419 -0.01985422 -0.12905239 rasiofsize 0.03795046*** -0.1740267 0.04643328*** 0.00272154 0.03795046*** 0.03795046*** rasioprof 0.22844817 0.5346437* 0.40959426* 0.40959013* 0.17225092 0.22844817 rasiolever 0.00677756 0.08528884 0.00446581 0.00446797 -0.00458034 0.00677756** rasiogrowth -0.12120495 0.20731754 0.05416822 0.05416028 0.05380034 -0.12120495 rasiocost 0.06415466 -0.02639971 0.0200552 0.0210875 -0.00320554 0.06415466* dwdsdgs8 (L1) 0.64593239*** _cons 0.07349114 -4.8364708 -0.46557147 -0.46413642 0.49222077 0.07349114 N 140 140 140 140 112 140 r2 0.30599457 0.15596912 0.27852448 - - 0.30599457 r2_a 0.26919125 -0.11733612 - - - 0.26919125 r2_o 0.270749 - - - - 0.270749 F / chi2 8.31432 2.771865 30.086592 31.946275 236.86882 280.9971 p 0.01011829 0.100005 0.0009155 0.0004156 0.0000 0.0000 Legend: * p<0.05; ** p<0.01; *** p<0.001 Table 5 shows the panel regression results using the Panel-Corrected Standard Errors (PCSE) method applied in response to the finding of autocorrelation and heteroscedasticity in the previous model. This PCSE method serves to correct the standard errors of the regression coefficients so that they remain valid despite the violation of these two classical assumptions. With this approach, the selected model still uses the Random Effect structure, but the estimation results become more robust and reliable, so that the significance test of the independent variable can be interpreted more accurately. The use of PCSE ensures that the conclusions drawn from the regression model are not distorted by inconsistencies in error variance or serial correlation between periods. Classical Assumption Test Classical assumption testing is carried out to ensure the validity of the panel regression model used in analyzing the effect of seven independent variables, namely, corporate governance, Unveiling the Drivers of SDGS 8 Disclosure: Evidence from Governance, Firm Characteristics, and Strategic Factors in Indonesian Listed Firms 1797 gender diversity, firm size, profitability, leverage, asset growth, and cost leadership strategy on the disclosure of SDG 8. In this study, four types of classical assumption tests were carried out, namely: Table 6 Normality Test Shapiro-Wilk W test for normal data Variable Obs W V z Prob > z res 140 0.98564 1.575 1.026 0.15243 Table 6 shows the test results obtained by the W statistical value of 0.98564 with a p- value of 0.1575 (p> 0.05). Because the p-value is greater than the 5% significance level (α = 0.05), the test decision is not to reject H₀, which means that the regression model residuals are normally distributed. These results indicate that the residual normality assumption in the panel data regression model is met. Satisfied residual normality indicates that the error distribution follows a normal distribution, so that the statistical test of the model parameters can be interpreted validly. Table 7. Multicollinearity Test VIF, Uncentered Variable VIF 1/VIF CLS 4.49 0.222871 GD 4.02 0.248520 PROFIT 2.36 0.424229 LEV 1.38 0.727007 FSIZE_c 1.36 0.732783 AGW 1.15 0.870413 CG_c 1.06 0.942436 Mean VIF 2.26 Multicollinearity test is conducted using Variance Inflation Factor (VIF). The test results show that all independent variables have VIF values below 5, with the highest value of 4.49 and an average VIF of 2.26. Since no variable has a VIF value above the threshold of 10, it can be concluded that there is no multicollinearity in the model. Thus, the relationship between the independent variables in this regression model does not show an adverse linear correlation, so the coefficient estimates can be said to be stable and can be interpreted properly. Table 8. Heteroscedasticity Test Coefficient: Generalizedleast squares Panels: homoskedastic Correlations: No autocorrelations Estimated covariences = 1 Number of obs = 140 Estimated autocorrelations = 0 Number of groups = 28 Estimated coefficients = 8 Time periods = 5 Wald chi2(7) = 62.08 American Journal of Economic and Management Business Vol. 4 No. 10 October 2025 1798 Log likelihood = 81.23169 Prob > chi2 = 0.0000 DWD_SDGs8 Coefficient Std. err z P>|z| [95% Conf. Interval] CG_c -0.4964474 0.2549093 -1.95 0.051 -0.9966065 0.0031658 GD -0.1315473 0.0847912 -1.55 0.121 -0.2977439 0.0346403 FSIZE_c 0.0377312 0.0085311 4.42 0.000 0.0210105 0.0544519 PROFIT 0.2319594 0.1418448 1.64 0.102 -0.0460577 0.5099764 LEV 0.068081 0.0651971 1.31 0.190 -0.0593728 0.196942 AGW 0.1214801 0.0681374 1.78 0.075 -0.0120667 0.2550268 CLS 0.0642795 0.0314689 2.04 0.041 0.0026016 0.1259574 _cons 0.7373514 0.029058 25.38 0.000 0.6803988 0.794304 Tabel 9. Uji Autokorelasi Linear regression, correlated panels corrected standard errors (PCSEs) Group Variable: NO Number of obs = 140 Time Variable: TAHUN Number of groups = 28 Panels: homoskedastic Obs per group : Autocoleration: No autocorrelations Min = 5 Avg = 5 Max= 5 Estimated covariences = 406 R Square = 0.3072 Estimated autocorrelations = 0 Wald chi2(7) = 282.85 Estimated coefficients = 8 Prob > chi2 = 0.00005 Panel-Corrected DWD_SDGs8 Coefficient Std. err z P>|z| [95% Conf. Interval] CG_c -0.4964474 0.1799518 -2.76 0.006 -0.8491465 -0.1437482 GD -0.1315473 0.0832305 -1.58 0.114 -0.294676 0.0315814 FSIZE_c 0.0377312 0.0061555 6.13 0.000 0.0256667 0.0497957 PROFIT 0.2319594 0.1476747 1.57 0.116 -0.0574784 0.5213973 LEV 0.068081 0.0222513 3.02 0.002 0.0249396 0.1112207 AGW 0.1214801 0.0567324 1.58 0.032 0.0103961 0.232568 CLS 0.0642795 0.0268912 2.39 0.017 0.0115733 0.1169857 _cons 0.7373514 0.0243407 30.29 0.000 0.6896446 0.7850583 After estimation using the Panel-Corrected Standard Errors (PCSE) approach to overcome potential heteroscedasticity and correlation between units, the results show that the model has met the assumption of free autocorrelation. This is indicated by the value of Estimated autocorrelations = 0, which indicates that there is no systematic relationship in the residuals between time periods. In this study, the Generalized Least Squares (GLS) approach with Panel-Corrected Standard Errors (PCSE) is used to overcome the potential heteroscedasticity identified at the initial stage of analysis. Based on the final estimation results, it is shown that the model has met the assumption of homoscedasticity, as explicitly stated in the model output: "Panels: homoskedastic". This indicates that the model is free from the problem of non-constant error variance. Thus, the estimated regression coefficients can be considered efficient and statistically valid. Unveiling the Drivers of SDGS 8 Disclosure: Evidence from Governance, Firm Characteristics, and Strategic Factors in Indonesian Listed Firms 1799 Thus, this panel regression model can be said to be temporally stable and feasible as a basis for drawing conclusions from the influence of each independent variable on the disclosure of decent work (SDG8). Regression Analysis Table 10. Simultaneous Test R-Squared = 0.3072 Wald chi2(7) = 282.85 Prob > chi2 = 0.0000 Table 10 shows the output results and obtained Wald value chi²(7) = 282.85 with probability level Prob > chi² = 0.0000. The probability value is far below the 5% significance level prob<00.5, indicating that the null hypothesis stating that all regressor coefficients are equal to zero simultaneously is rejected. Thus, it can be concluded that overall, the independent variables in the model have a significant influence on decent work disclosure (SDG 8). In addition, the R-squared value of 0.3072 indicates that about 30.72% of the variation in the disclosure of SDGs 8 can be explained by the independent variables in the model. Although the value is not very high, it still indicates a substantive contribution of the model in explaining the phenomenon under study. Table 11 Partial Test Panel-Corrected DWD_SDGs8 Coefficient Std. err z P>|z| [95% Conf. Interval] CG_c -0.4964474 0.1799518 -2.76 0.006 -0.8491465 -0.1437482 GD -0.1315473 0.0832305 -1.58 0.114 -0.294676 0.0315814 FSIZE_c 0.0377312 0.0061555 6.13 0.000 0.0256667 0.0497957 PROFIT 0.2319594 0.1476747 1.57 0.116 -0.0574784 0.5213973 LEV 0.068081 0.0222513 3.02 0.002 0.0249396 0.1112207 AGW 0.1214801 0.0567324 1.58 0.032 0.0103961 0.232568 CLS 0.0642795 0.0268912 2.39 0.017 0.0115733 0.1169857 _cons 0.7373514 0.0243407 30.29 0.000 0.6896446 0.7850583 Table 11 shows the partial test results that deepen the analysis by showing the effect of each variable partially on decent work disclosure. The results reveal that only four of the seven variables are statistically significant, namely corporate governance (negative effect), firm size, leverage, and cost leadership strategy (all three positive effects). This finding highlights that variables representing external pressures and firms' strategic need to maintain legitimacy are more dominant in driving SDG 8 disclosures. Corporate governance and decent work (SDG8) Corporate governance has a coefficient of -0.4964 with a probability of 0.006, which is smaller than the 5% significance level (0.006 < 0.05), the null hypothesis (H₀) is rejected and the alternative hypothesis (Hₐ) is accepted. This indicates a negative influence between the quality American Journal of Economic and Management Business Vol. 4 No. 10 October 2025 1800 of corporate governance and the disclosure of decent work. The higher the governance score, the lower the level of SDGs 8 reporting. This finding suggests that companies with high governance systems tend to be more selective or limit the information they disclose to the public, including in terms of employment. This presents an interesting dynamic and contradicts the theoretical assumption and initial hypothesis that good corporate governance should encourage increased transparency. In this context, legitimacy theory, particularly through the concept of legitimacy gap, provides a relevant explanation. Governance practices in many companies, especially in developing countries such as Indonesia, especially non-financial companies listed on the IDX for the period 2019 to 2023, tend to be carried out normatively or formalistically and oriented towards minimum regulatory compliance, not because of an internal drive to address sustainability issues substantively (Suchman, 1995; Galeazzo et al., 2024). When basic CG principles such as accountability, independence and transparency are only applied administratively, real social legitimacy is not achieved. As a result, disclosure of labor issues in the framework of SDGs 8 is not a priority, in the context of corporate governance that is still oriented towards compliance. Gender Diversity and decent work (SDG8) Gender diversity has a coefficient of -0.1315 and a p-value of 0.114 > 0.05, the null hypothesis (H₀) is accepted and the alternative hypothesis (Hₐ) is rejected. The results show that gender diversity in the company's board of directors or management has no effect on the level of disclosure of information related to decent work. Although theoretically gender diversity is expected to strengthen corporate social sensitivity (Arayssi et al., 2020; Raimo et al., 2021), in the context of non-financial companies in Indonesia, women's representation is still limited and tends to be symbolic (tokenism). This is in line with the findings of Monteiro et al. (2022), which state that gender diversity has not been the main driving force in social reporting practices if it is not supported by strategic authority or key positions in the decision-making structure. This causes their contribution to social disclosure has not been realized in real terms. Based on legitimacy theory (Suchman, 1995; Deegan, 2002), the presence of women on boards can be used as a symbolic strategy to gain public acceptance, but does not guarantee strengthening disclosure. From the perspective of stakeholder theory (Freeman, 1984), the dominance of power in the board and the weak position of women in the decision-making structure are factors inhibiting the effectiveness of gender diversity in encouraging transparency. Firm size and decent work (SDG8) Firm Size (Fsize) has a coefficient of 0.0377 with a significance value of 0.000 < 0.05, so the null hypothesis (H₀) is rejected and the alternative hypothesis (Hₐ) is accepted. Thus, it can be concluded that company size has a significant positive effect on the disclosure of decent work (SDGs 8) in non-financial sector companies listed on the IDX for the period 2019-2023. This finding shows that companies with a larger scale tend to have better reporting capacity because they are supported by the availability of adequate financial, human and information system resources (Dilling & Caykoylu, 2019; Sumiani et al., 2020). In addition, large companies are more Unveiling the Drivers of SDGS 8 Disclosure: Evidence from Governance, Firm Characteristics, and Strategic Factors in Indonesian Listed Firms 1801 open to external pressures from regulators, investors and the wider community that demand transparency on social performance, including labor aspects. Within the framework of legitimacy theory, these conditions encourage large companies to increase sustainability disclosures to maintain public trust and a positive corporate reputation. Profitability and decent work (SDG8) Profitability (PROFIT) has a coefficient of 0.2319 with a significance value of 0.116 > 0.05, so the null hypothesis (H₀) is accepted and the alternative hypothesis (Hₐ) is rejected. Thus, it can be concluded that profitability has no significant effect on the disclosure of decent work (SDGs 8) in non-financial sector companies listed on the IDX for the 2019-2023 period. This finding is consistent with the results of research by Saha et al. (2023) and Beretta et al. (2025) which state that financial performance is not the main determinant in encouraging sustainability disclosure, including labor aspects. Companies that have high profits may not necessarily show a commitment to social transparency, as they are more focused on business expansion or operational efficiency. Conversely, companies with low profitability may be encouraged to disclose labor information in response to external pressures, such as regulations, investor demands, and public expectations. This suggests that the motivation to disclose SDGs 8 is more influenced by social legitimacy factors and stakeholder pressure than by the internal financial strength of the company. Leverage and decent work (SDG8) Leverage (LEV) has a coefficient of 0.0068 with a significance value of 0.002 (< 0.05), so the null hypothesis (H₀) is rejected and the alternative hypothesis (Hₐ) is accepted. Thus, it can be concluded that leverage has a significant positive effect on the disclosure of decent work (SDGs 8) in non-financial sector companies listed on the IDX for the 2019-2023 period. This means that the higher the level of corporate debt, the greater the tendency of companies to increase social transparency as a form of responsibility to the public and lenders. In the perspective of legitimacy theory (Suchman, 1995; Deegan, 2002), companies that have a high liability burden face greater external pressure to demonstrate a commitment to decent labor practices. In addition, companies with high levels of debt usually face greater pressure from creditors and financing institutions, which demand transparency as a form of risk management and assurance of business continuity (Dhingra et al., 2022; Freeman, 1984). Under these conditions, social reporting, especially related to labor issues, can serve as a strategic tool to demonstrate the company's commitment to social responsibility and sustainability, while building the trust of financial stakeholders. Therefore, increased disclosure in highly leveraged companies reflects a response to external pressures, rather than being driven by internal performance, so that reporting becomes part of an external reputation and legitimacy risk management strategy. Asset Growth and decent work (SDG8) Asset growth (AGW) has a coefficient of 0.1215 with a significance value of 0.114 > 0.05, so the null hypothesis (H₀) is accepted and the alternative hypothesis (Hₐ) is rejected. Thus, American Journal of Economic and Management Business Vol. 4 No. 10 October 2025 1802 it can be concluded that asset growth has no significant effect on the disclosure of decent work (SDGs 8) in non-financial sector companies listed on the IDX for the 2019-2023 period. This finding is in line with the research of Maama and Gani (2022) and Kılıç and Kuzey (2019) which show that asset growth or company expansion does not always correlate with increased disclosure of social responsibility, including labor aspects. Companies with high asset growth often focus more on operational efficiency and market expansion, rather than on improving sustainability reporting. Conversely, companies with lower asset growth may still be compelled to make social disclosures due to external pressures or regulatory obligations. Thus, external factors such as stakeholder pressure and social legitimacy remain the main drivers of SDGs 8 disclosure rather than asset growth itself. Cost Leadership and decent work (SDG8) Cost leadership (CLS) has a coefficient of 0.0643 with a significance level of 0.017 (< 0.05), so the null hypothesis (H₀) is rejected and the alternative hypothesis (Hₐ) is accepted. Thus, it can be concluded that the cost leadership strategy has a significant positive effect on the disclosure of decent work (SDGs 8) in non-financial sector companies listed on the IDX for the period 2019-2023. This finding shows that cost efficiency is not always an obstacle to transparency, but can actually increase the company's capacity to meet social reporting demands. This strategy encourages more systematic resource management, thus supporting more active sustainability reporting. This result is in line with the research of Abdelqader et al. (2024) and Azzahra and Widiastuty (2025) which state that a low cost strategy can contribute positively to sustainability performance and corporate legitimacy. And research by Majidah and Sakina (2023) shows that a cost leadership strategy can support the achievement of sustainability goals without hindering corporate transparency, including in the disclosure of labor aspects. In the context of SDGs 8, companies that apply cost leadership tend to utilize labor reporting as a strategic tool to strengthen reputation and demonstrate commitment to social sustainability. CONCLUSION The rising number of issuers on the Indonesia Stock Exchange has not been matched by improvements in employment quality, underscoring the importance of transparency in decent work issues to sustain corporate–stakeholder credibility. This study found that corporate governance had a negative effect on decent work disclosure, while firm size, leverage, and cost leadership strategies encouraged higher disclosure, suggesting that external pressures for efficiency and legitimacy carry more weight than internal governance practices in shaping SDG 8 reporting. 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