Impact of ESG Disclosure Quality on Reputation-Performance of Vietnamese Firms

By Duc Trong Tran, Bao Ngan Nguyen, Phuong Anh Truong, Chau Anh Dinh, and Phuong Nhi Le

National Economics University, Vietnam

Cite as: Tran, D. T.; Nguyen, B. N.; Truong, P. A.; Dinh, C. A. and Le, P. N. (2026), "Impact of ESG Disclosure Quality on Reputation-Performance of Vietnamese Firms", International Journal of Management and Applied Research, Vol. 13, No. 1, pp. 1-20. https://doi.org/10.18646/2056.131.26-001 | Download PDF

Abstract

This study investigates the determinants and consequences of ESG disclosure quality in Vietnamese enterprises, with particular emphasis on its impact on corporate reputation and firm performance. Grounded in stakeholder theory and the resource-based view, the study develops an integrated research model that examines both antecedent factors influencing ESG disclosure quality and its subsequent performance outcomes. Data were collected through a mixed-method approach, combining expert interviews and a quantitative survey of 314 valid responses from managers and employees of Vietnamese import-export firms. The proposed model was tested using partial least squares structural equation modeling (PLS-SEM). The findings reveal that ESG disclosure quality is positively driven by internal and institutional factors, and it exerts a significant positive effect on both corporate reputation and firm performance. Moreover, corporate reputation plays a partial mediating role in the relationship between ESG disclosure quality and firm performance. Firm size shows a significant control effect, while industry type does not significantly influence performance outcomes. Overall, the results highlight ESG disclosure as a strategic resource that enhances reputational capital and improves operational effectiveness, offering important implications for Vietnamese import-export enterprises in the context of global sustainability requirements.

1. Introduction

In the context of deepening international economic integration, disclosure of Environmental, Social, and Governance (ESG) - a framework used to evaluate a company’s sustainability and ethical impact beyond traditional financial metrics has become an essential standard for demonstrating corporate responsibility and competitiveness. In Vietnam, enterprises face increasing pressure from emerging global trade standards, particularly stringent ESG transparency requirements such as the European Union’s Carbon Border Adjustment Mechanism (CBAM) and the European Sustainability Reporting Standards (ESRS). Although the Vietnamese government has introduced various sustainability-related policies, ESG practices remain limited, especially among small and medium-sized enterprises due to constraints in data availability, specialized human resources, and standardized reporting systems.

The academic literature increasingly conceptualizes ESG disclosure as a strategic governance mechanism rather than a symbolic reporting exercise. Early studies emphasize sustainability reporting as a response to institutional and stakeholder pressures aimed at maintaining organizational legitimacy (Gray et al., 1995), while subsequent research highlights the pioneering role of multinational corporations in adopting international reporting standards to meet diverse stakeholder expectations (Kolk, 2008). More recent studies underscore the shift from CSR to ESG, emphasizing the integration of environmental, social, and governance factors into core business strategy to create long-term firm value (Passas et al., 2024), while also cautioning against ESG washing and inconsistent disclosure practices, thereby stressing the importance of disclosure quality over quantity (Hummel & Schlick, 2016). In Vietnam, existing evidence mainly focuses on listed firms and financial institutions, leaving the mediating role of corporate reputation largely under explored. Against this backdrop, this study examines the impact of ESG disclosure quality on corporate reputation and firm performance among Vietnamese enterprises.

In Vietnam, existing studies on ESG disclosure primarily focus on listed firms and measure firm performance through financial indicators, while the impact of ESG disclosure quality on enterprises and particularly on corporate reputation remains insufficiently examined. Addressing this research gap, the present study investigates the effects of ESG disclosure quality on corporate reputation and firm performance among Vietnamese enterprises, thereby offering implications for enhancing competitiveness in the context of global economic integration.

2. Literature review

2.1. ESG Disclosure

In recent years, ESG has emerged as a key evaluative framework guiding corporate development, not only complementing financial performance but also reflecting firms’ risk management capabilities and long-term sustainability. ESG comprises three pillars: Environmental (E), which relates to the management of ecological impacts; Social (S), which reflects responsibility toward employees, customers, and the broader community; and Governance (G), which focuses on managerial mechanisms, transparency, and compliance (Li et al., 2021).ESG is widely regarded as an extension of corporate social responsibility (CSR), representing a shift from a shareholder-centered approach toward a multi-stakeholder orientation (Carroll and Shabana, 2010). ESG disclosure is therefore not merely ethical in nature but also generates tangible business benefits, such as risk reduction, enhanced corporate reputation, and increased firm value. According to Tsang et al. (2022), the motivations for ESG disclosure can be explained through stakeholder theory, legitimacy theory, and signaling theory. Moreover, ESG disclosure quality reflected in the completeness, reliability, and comparability of information-plays a crucial role in strengthening investor confidence and reducing the cost of capital (Stuart et al., 2022).

The measurement and assessment of ESG disclosure play a vital role in sustainable governance research, as they reflect the degree of corporate transparency and accountability toward stakeholders. The Global Reporting Initiative (GRI) standards are currently considered the most widely adopted reporting framework, as they help standardize the disclosure of economic, social, and environmental impacts, thereby enhancing the quality of non-financial information and investor trust. Prior studies indicate that ESG disclosure can be evaluated in terms of both the extent of disclosure and the quality of disclosure. Disclosure quality captures the depth, specificity, and reliability of information, rather than merely the number of indicators reported. Accordingly, ESG measurement should clearly distinguish between the scope of disclosure and the level of substantive transparency to ensure comparability and the practical usefulness of ESG information.

2.2. Information Technology Systems and ESG Disclosure Quality

Consistent empirical evidence indicates that the capability of Information Technology (IT) systems plays a fundamental role in enhancing the quality of ESG disclosure. Studies by Duran et al. (2023) and Asif (2023) demonstrate that investment in robust financial-technological data infrastructure enables firms to collect, store, and process ESG-related data more effectively, thereby significantly improving the transparency and reliability of ESG reporting. Strong IT systems help minimize errors, standardize data governance processes, and enhance firms’ ability to comply with international reporting standards.

Furthermore, Lyu et al. (2025) and Marczewska et al. (2025) emphasize the positive impact of technological innovation capability and internal digital capability. Firms with the capacity to develop new technologies, implement integrated data systems, utilize advanced reporting software, and apply efficient automation processes tend to achieve higher levels of completeness and transparency in ESG disclosure. Therefore, the hypothesis is proposed:

H1: Information Technology Systems will positively affect ESG Disclosure Quality.

2.3. Use Of Artificial Intelligenceand ESG Disclosure Quality

Use Of Artificial Intelligence (AI) is regarded as a transformative tool that enables firms to enhance the quality of ESG disclosure by improving regulatory compliance, reliability, and transparency. Hillebrand et al. (2023) and Peng et al. (2023) affirm that AI supports regulatory compliance by benchmarking corporate reports against established reporting frameworks and detecting data inconsistencies, thereby mitigating the risk of “greenwashing.”

Joshi (2023), Rangarajan et al. (2025)show that AI enables the automation of data collection, verification, and processing from multiple sources (such as large language models (LLMs), machine learning techniques, and the Internet of Things (IoT)), which enhances the completeness and timeliness of ESG reporting. Data accuracy can be significantly improved compared to manual approaches. In addition, Choi and Kim (2023) indicate that AI facilitates the visualization and summarization of complex ESG data, making such information more accessible and easier to evaluate for stakeholders. Therefore, the hypothesis is proposed:

H2: Use Of Artificial Intelligencewill positively affect ESG Disclosure Quality.

2.4. Financial Capability and ESG Disclosure Quality

Financial capability (commonly measured by profitability indicators such as ROA) is considered an important organizational resource that influences firms’ ability to invest in sophisticated ESG reporting systems. Numerous studies support a positive relationship. Ferdous et al. (2025) and Sulaiman et al. (2025) consistently show that higher profitability enables firms to invest in more comprehensive ESG reporting systems, thereby enhancing transparency and corporate credibility.

However, evidence from emerging markets presents mixed or insignificant results. Studies in Saudi Arabia (Basali, 2025) and China (Liu and Lee, 2024) report contradictory findings, and in some cases even a negative association, particularly with the governance pillar. These results suggest that in markets where external institutional pressure is relatively weak, higher profitability may be directed toward short-term financial objectives or earnings management rather than improving ESG transparency. Therefore, the hypothesis is proposed:

H3: Financial Capability will positively affect ESG Disclosure Quality.

2.5. Growth Opportunity and ESG Disclosure Quality

Growth opportunity reflects a firm’s potential for future business expansion. Early studies (e.g., Craswell and Taylor, 1992; Lang and Lundholm, 1993) argue that firms with strong growth potential tend to be more proactive in voluntary disclosure, including ESG information, in order to reduce information asymmetry and the cost of capital.

However, Hassani and Bahini (2022) offer a more strategic perspective, suggesting that firms with high growth opportunities do not necessarily pursue full transparency. Instead, they may disclose ESG information only up to an optimal level that helps lower the cost of capital, while withholding certain strategic information to protect the competitive advantages of their growth projects. Therefore, the hypothesis is proposed:

H4: Growth Opportunities will positively affect ESG Disclosure Quality.

2.6. Managerial Mindset and ESG Disclosure Quality

Managerial mindset, reflected through board structure and monitoring mechanisms, represents a key internal factor influencing ESG disclosure quality. Studies by Meng (2023) and Nicolo et al. (2023) consistently document a strong positive relationship. Transparent and effective internal governance structures-characterized by independent boards, gender diversity, and the presence of CSR committees-are widely regarded as manifestations of a governance mindset oriented toward sustainability.

Septiana and Puspawati (2022) further reinforce this view by showing that independent directors and remuneration committees have a positive impact on ESG disclosure in Southeast Asian countries. Therefore, the hypothesis is proposed:

H5: Managerial Mindset will positively affect ESG Disclosure Quality.

2.7. Regulatory Framework and ESG Disclosure Quality

Regulatory framework is regarded as a critical external factor influencing the quality of corporate ESG disclosure. Lukács (2025) argues that mandatory regulations help standardize information, reduce managerial discretion, and enhance the accuracy of ESG data through transparent reporting guidelines. Empirical studies by Krueger et al. (2024), Wattanatorn (2025), and Khamisu (2024) consistently confirm that mandatory regulatory requirements increase the frequency, volume, and quality of ESG disclosure, particularly in emerging economies and among firms with relatively low ESG performance.

In Vietnam, Nguyen (2024) emphasizes the role of legal regulations in integrating ESG considerations into corporate governance, thereby improving the completeness, accuracy, and reliability of ESG reporting. Similarly, a report by the CFA Institute (2023) in Europe shows that mandatory legal standards, along with enforcement and sanctioning mechanisms, reduce discretion in disclosure practices and enhance the comparability and credibility of ESG information. These findings provide important implications for emerging markets such as Vietnam. Therefore, the hypothesis is proposed:

H6: Regulatory Framework will positively affect ESG Disclosure Quality.

2.8. ESG Disclosure Quality and Corporate Reputation

A substantial body of research confirms that ESG disclosure quality plays a crucial role in building and strengthening corporate reputation. Siwei (2023) and Yang et al. (2022) show that transparent and consistent ESG disclosure helps reduce information asymmetry and enhance the trust of investors and the public, thereby increasing corporate reputation and firm value. This effect is particularly pronounced among non-state-owned enterprises. Studies by Wang et al. (2024) further confirm that high-quality ESG disclosure functions as a reputation management tool, enabling firms to cultivate a credible corporate image and strengthen brand reputation, especially in emerging markets.

In the Vietnamese context, Ha, Nguyen, and Ho (2024) find that ESG disclosure quality has a positive impact on corporate reputation as reflected in stock price reactions, with the environmental pillar being the most highly valued by the market. The PwC Vietnam ESG Readiness 2022 report also indicates that firms with higher ESG readiness and more transparent and frequent ESG disclosure are perceived more favorably by stakeholders in terms of trust and reputation. Therefore, the hypothesis is proposed:

H7: ESG Disclosure Quality will positively affect Corporate Reputation.

2.9. Corporate Reputation as Mediator Between ESG Disclosure Quality and Firm Performance

Corporate reputation is widely regarded as a critical intangible asset that positively influences firm performance. Lee and Roh (2012) demonstrate that firms with strong reputations tend to achieve more stable profitability, market value, and overall operating performance. A global study by Pham and Tran (2020) further confirms that corporate reputation plays an important mediating role by transforming the effects of ESG/CSR disclosure into improved firm performance through enhanced stakeholder trust and reduced cost of capital.

In the Vietnamese context, studies by Nguyen (2020), Nguyen and Le (2021), and Kieu (2024) consistently indicate that corporate reputation serves as a key intangible resource that strengthens stakeholder confidence, improves profitability and financial performance, and enhances firms’ competitive capacity. Therefore, the hypothesis is proposed:

H8: Corporate Reputation will positively affect Firm Performance.

2.10. ESG Disclosure Quality and Firm Performance

Prior studies indicate that ESG disclosure quality has a significant impact on firm performance, although the empirical evidence remains mixed. Tao (2023) and Bamel (2025) both confirm that high-quality ESG disclosure positively affects firm performance, albeit with varying magnitudes across industries and markets. In the import-export sector, Wu et al. (2022) and Sun and Li (2024) find that ESG practices enhance export intensity, domestic value added, and international competitiveness through channels such as innovation and the alleviation of financial constraints.

In contrast, Khandelwal (2023) identifies a negative relationship between ESG disclosure quality and firm performance, suggesting that ESG disclosure, when symbolic or poorly aligned with firm strategy, may reduce profitability. These conflicting findings imply that the effect of ESG disclosure quality on firm performance is context-dependent and contingent on how ESG practices are implemented, thereby highlighting the need for more in-depth investigation within specific settings. Therefore, the hypothesis is proposed:

H9: ESG Disclosure Quality will positively affect Firm Performance.

The proposed research model for the study is presented in Figure 1.

Figure 1: Proposed research model
Proposed research model

3. Methodology

3.1. Sample and Data Collection

This study employed a quantitative research design to test the proposed measurement scales and structural model examining the impact of ESG disclosure quality on corporate reputation and firm performance in Vietnamese enterprises. Data were collected between July and October 2025 using a structured questionnaire administered through both online and direct distribution methods.

Given the difficulty in accessing enterprises, a non-probability snowball sampling technique was adopted to facilitate data collection while ensuring efficiency in terms of time and cost. Based on recommendations for EFA and PLS-SEM, the minimum sample size was determined to be 4 - 10 times the number of observed variables. To enhance statistical reliability, a total of 341 questionnaires were distributed, of which 314 valid responses were retained after excluding incomplete or invalid surveys.

Descriptive statistics indicate a relatively balanced gender distribution (53.2% female, 46.8% male). Most respondents were aged between 21 and 40 years (78%), held at least a bachelor’s degree (70.7%), and worked primarily as staff or specialists (89.5%). Nearly half had 5 - 10 years of experience in their sector. The surveyed firms were mainly manufacturing enterprises (72.6%), operating for 5 - 10 years, with fewer than 500 employees, and located predominantly in the Red River Delta and Southeast regions.

3.2. Measurements

All constructs in this study were measured using multi-item scales adapted from prior validated studies and assessed on a five-point Likert scale ranging from 1 (“strongly disagree”) to 5 (“strongly agree”).

Use of Artificial Intelligence was measured using six items adapted from Riyath and Jariya (2024), capturing strategic alignment, human resource development, infrastructure investment, change and risk management, and data governance. Information Technology Systems were assessed with five items from Nguyen et al. (2024), focusing on ESG-related IT infrastructure, software, automation, system updates, and cybersecurity. Financial Capacity was measured using five items adapted from Panakaje et al. (2025), reflecting financial planning, flexibility, and investment capability in ESG initiatives. Growth Opportunity was measured with three items from Wolff et al. (2015), capturing perceived growth in customers, revenue, and market share. Managerial Mindset was assessed using five items adapted from Mensah et al. (2024), Le and Govindan (2024), and Achmad and Wiratmadja (2024), reflecting ESG-oriented thinking, ethical responsibility, and strategic integration of ESG. Regulatory Framework was measured with five items adapted from Wu and Tham (2023) and Lee et al. (2024), capturing the clarity, enforcement, and stringency of ESG-related regulations. ESG Disclosure Quality was assessed using nine items from Cheng and Huang (2024), evaluating the completeness, transparency, reliability, and timeliness of ESG information. Corporate Reputation was measured with six items adapted from Nkgowe et al. (2025), reflecting trustworthiness, compliance, social responsibility, and customer orientation. Firm Performance was assessed using seven items adapted from Arda et al. (2018) and Cantele and Cassia (2020), capturing financial and market performance, competitiveness, supply chain efficiency, and innovation capability. A pilot test was conducted with respondents sharing characteristics of the study population to ensure the clarity and reliability of the measurement items. The results indicated satisfactory internal consistency, with Cronbach’s alpha coefficients exceeding the recommended threshold of 0.70, confirming the reliability of the measurement scales used in this study.

3.3. Data Analysis

This study employed Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS 4 to test the proposed research model. PLS-SEM is suitable for analyzing complex models and data characteristics that deviate from normality (Hair et al., 2014). The analysis followed two main stages. First, the reflective measurement model was evaluated in terms of indicator reliability (outer loadings ≥ 0.7), internal consistency (Cronbach’s alpha and composite reliability ≥ 0.7), convergent validity (average variance extracted - AVE ≥ 0.5), and discriminant validity using the Fornell - Larcker criterion and the Heterotrait–Monotrait ratio (HTMT ≤ 0.9). Second, the structural model was assessed by examining multicollinearity through variance inflation factors (VIF < 5), the significance of path coefficients using p-values (p < 0.05), explanatory power via R² and adjusted R², and effect sizes using f² to determine the magnitude of relationships among constructs.

4. Results

4.1. Common Method Bias (CMB)

Common method bias may arise when variance in the data is driven more by the measurement method than by the constructs themselves (Podsakoff et al., 2003). To assess this issue, an exploratory factor analysis (EFA) was conducted simultaneously on all measurement items using principal component extraction with Varimax rotation. The results show that nine factors with eigenvalues greater than 1 was extracted, explaining 68.139% of the total variance. Importantly, the first factor accounted for 29.826% of the variance, which is well below the 50% threshold commonly used to indicate serious common method bias. In addition, all retained items loaded strongly on their intended factors (factor loadings > 0.5) and did not exhibit substantial cross-loadings.

4.2. Measurement Model Assessment

Indicator reliability was evaluated using outer loadings in the PLS-SEM measurement model. Following Hair et al. (2014, 2021), indicators with loadings ≥ 0.70 were considered acceptable. The results show that all indicators exhibited outer loadings above 0.70, ranging from 0.705 to 0.945, indicating that each indicator explained more than 50% of the variance of its corresponding construct. Therefore, no indicator was removed from the model.

Table 1: Outer loadings
AIU CR EDQ FP FC GO IT MM RF
AIU1
AIU2
AIU3
AIU4
AIU5
AIU6 		0.838
0.823
0.833
0.861
0.861
0.803
CR1
CR2
CR3
CR4
CR5
CR6 		0.864
0.867
0.868
0.908
0.825
0.862
EDQ1
EDQ2
EDQ3
EDQ5
EDQ6
EDQ7
EDQ8
EDQ9		 0.705
0.744
0.761
0.808
0.726
0.798
0.781
0.719
FP1
FP2
FP3
FP4
FP5
FP6 		0.759
0.835
0.799
0.797
0.831
0.771
FC1
FC3
FC4
FC5 		0.857
0.863
0.776
0.859
GO1
GO2
GO3 		0.945
0.818
0.830
IT1
IT2
IT3
IT4
IT5 		0.768
0.782
0.801
0.818
0.829
MM1
MM2
MM3
MM4
MM5 		0.827
0.745
0.743
0.812
0.815
RF1
RF2
RF3
RF4
RF5 		0.814
0.852
0.818
0.775
0.829

Internal consistency reliability was assessed using Cronbach’s alpha and Composite Reliability (CR) in Table 2. As reported in Table X, Cronbach’s alpha values ranged from 0.848 (MM) to 0.933 (CR), while CR values (rho_c) ranged from 0.892 (MM) to 0.947 (CR), all exceeding the recommended threshold of 0.70. Convergent validity was examined using the Average Variance Extracted (AVE). The AVE values for all constructs were above the minimum criterion of 0.50, ranging from 0.572 (EDQ) to 0.751 (GO).

Table 2: Construct reliability and validity
Cronbach's alpha Composite reliability (rho_a) Composite reliability (rho_c) Average variance extracted (AVE)
AIU 0.915 0.931 0.933 0.700
CR 0.933 0.935 0.947 0.750
EDQ 0.893 0.897 0.914 0.572
FP 0.887 0.890 0.914 0.639
FC 0.862 0.886 0.905 0.704
GO 0.854 1.149 0.900 0.751
IT 0.860 0.868 0.899 0.640
MM 0.848 0.853 0.892 0.623
RF 0.876 0.880 0.910 0.669

Discriminant validity was assessed using both the Fornell-Larcker criterion and the Heterotrait - Monotrait ratio (HTMT) in Table 3 and Table 4. The square roots of AVE for all constructs (ranging from 0.756 to 0.866) were greater than the corresponding inter-construct correlations. Additionally, all HTMT values were below the conservative threshold of 0.90, with values ranging from 0.029 to 0.710.

Table 3: Discriminant validity - Fornell and Larcker criterion
AIU CR EDQ FP FC GO IT MM RF
AIU 0.837
CR 0.524 0.866
EDQ 0.499 0.456 0.756
FP 0.416 0.461 0.638 0.799
FC 0.322 0.349 0.464 0.387 0.839
GO -0.035 -0.054 0.025 0.042 0.002 0.866
IT 0.207 0.112 0.360 0.296 0.305 -0.081 0.800
MM 0.307 0.357 0.462 0.318 0.359 -0.036 0.199 0.789
RF 0.449 0.387 0.607 0.453 0.383 -0.020 0.279 0.428 0.818


Table 4: Discriminant validity - Heterotrait-monotrait ratio (HTMT)
AIU CR EDQ FP FC GO IT MM RF
AIU
CR 0.560
EDQ 0.527 0.489
FP 0.449 0.498 0.710
FC 0.341 0.376 0.511 0.431
GO 0.065 0.060 0.077 0.077 0.029
IT 0.219 0.121 0.407 0.333 0.342 0.104
MM 0.346 0.399 0.526 0.362 0.409 0.063 0.224
RF 0.490 0.422 0.678 0.509 0.424 0.033 0.318 0.496

4.3. Structural Model Assessment

The structural model was assessed in terms of collinearity, the significance of hypothesized relationships, explanatory power, and effect sizes following the PLS-SEM procedure (Hair et al., 2021).

Figure 2: Path Analysis
Path Analysis

Collinearity was examined using the variance inflation factor (VIF). The inner VIF values in Table 5 ranged from 1.000 to 1.508, all well below the conservative threshold of 3.0, indicating that multicollinearity was not a concern in the structural model. Thus, the estimated path coefficients were not biased by collinearity issues.

Table 5: Collinearity statistics (VIF) - Inner model
AIU CR EDQ FP FC GO IT MM RF
AIU 1.314
CR 1.263
EDQ 1.000 1.263
FP
FC 1.324
GO 1.009
IT 1.154
MM 1.312
RF 1.508

Hypothesis testing was conducted using the bootstrapping procedure in SmartPLS shown in Table 6. The results show that most structural paths were statistically significant at the 5% level. Specifically, Information Technology Systems (β = 0.143, p = 0.002), Use of Artificial Intelligence (β = 0.216, p < 0.001), Financial Capacity (β = 0.162, p < 0.001), Managerial Mindset (β = 0.166, p = 0.001), and Regulatory Framework (β = 0.338, p < 0.001) all had positive and significant effects on ESG Disclosure Quality, supporting H1, H2, H3, H5, and H6. In contrast, Growth Opportunity → ESG Disclosure Quality was not significant (β = 0.057, p = 0.232), leading to the rejection of H4.

Regarding downstream effects, ESG Disclosure Quality significantly influenced Corporate Reputation (β = 0.456, p < 0.001) and Firm Performance (β = 0.540, p < 0.001), supporting H7 and H9. In addition, Corporate Reputation had a significant positive effect on Firm Performance (β = 0.215, p < 0.001), supporting H8.

Table 6: Path coefficients - Mean, STDEV, T values, p values
Original sample (O) Sample mean (M) Standard deviation (STDEV) T statistics (|O/STDEV|) P values
AIU -> EDQ 0.216 0.219 0.049 4.409 0.000
CR -> FP 0.215 0.211 0.057 3.757 0.000
EDQ -> CR 0.456 0.457 0.056 8.141 0.000
EDQ -> FP 0.540 0.544 0.052 10.329 0.000
FC -> EDQ 0.162 0.161 0.045 3.614 0.000
GO -> EDQ 0.057 0.053 0.047 1.196 0.232
IT -> EDQ 0.143 0.141 0.047 3.061 0.002
MM -> EDQ 0.166 0.166 0.051 3.234 0.001
RF -> EDQ 0.338 0.336 0.047 7.204 0.000

The explanatory power of the model was assessed using the coefficient of determination (R²) in Table 7. The adjusted R² values indicate that the model explains 50.8% of the variance in ESG Disclosure Quality, 20.6% of the variance in Corporate Reputation, and 44.0% of the variance in Firm Performance.

Table 7: Coefficient of determination (R²)
R-square R-square adjusted
CR 0.208 0.206
EDQ 0.518 0.508
FP 0.444 0.440

Effect size (f²) analysis in Table 8 shows that ESG Disclosure Quality had a strong effect on Firm Performance (f² = 0.415) and a moderate effect on Corporate Reputation (f² = 0.263). The Regulatory Framework → ESG Disclosure Quality relationship also exhibited a moderate effect size (f² = 0.157). All remaining significant relationships showed small effect sizes (f² ranging from 0.037 to 0.074), while Growth Opportunity → ESG Disclosure Quality demonstrated a negligible effect (f² = 0.007).

Table 8: Effect size (f²)
AIU CR EDQ FP FC GO IT MM RF
AIU 0.074
CR 0.066
EDQ 0.263 0.415
FP
FC 0.041
GO 0.007
IT 0.037
MM 0.044
RF 0.157

5. Discussion

This study examines the determinants and consequences of ESG disclosure quality in Vietnamese firms. The findings confirm that information technology systems, artificial intelligence adoption, financial capacity, managerial mindset, and regulatory framework all exert significant positive effects on ESG disclosure quality.

In contrast, growth opportunity does not directly influence ESG disclosure quality, implying that expansion potential alone does not incentivize firms to enhance transparency unless accompanied by a clear sustainability strategy.

The results also demonstrate that ESG disclosure quality positively affects both corporate reputation and firm performance. High-quality ESG disclosure reduces information asymmetry, strengthens stakeholder trust, and enhances firms’ legitimacy in international markets. Furthermore, ESG disclosure contributes directly to operational efficiency and competitiveness, highlighting its strategic rather than symbolic role. Corporate reputation, in turn, positively influences firm performance, confirming its function as an intangible asset that translates transparency and credibility into economic outcomes.

5.1. Theoretical and Practical Implications

This study extends ESG disclosure literature by integrating technological capability, governance orientation, and regulatory pressure into a unified framework explaining ESG disclosure quality in Vietnamese firms. It provides empirical evidence from an emerging economy, addressing a notable gap in ESG research dominated by developed-market contexts. The findings also clarify the mediating role of ESG disclosure quality in linking internal capabilities to reputation and performance.

This study provides important practical contributions for leaders and managers in Vietnam. The results highlight that ESG disclosure quality should be treated as a strategic governance tool rather than a compliance exercise. Investments in IT infrastructure, AI-enabled data management, and financial planning are essential to ensure reliable and verifiable ESG reporting. Strengthening managerial commitment to ESG principles is equally critical. Policymakers should accelerate the development of a coherent and mandatory ESG reporting framework. Industry associations can facilitate ESG capacity building through standardized guidelines, shared platforms, and affordable verification services.

5.2. Limitations and Future Research

This study has several limitations that should be addressed in future research. First, the use of non-probability sampling limits the generalizability of the findings. Second, the cross-sectional design restricts causal inference. Third, the measurement of AI adoption reflects early-stage implementation and may underestimate its long-term impact. Future research should employ longitudinal designs, probability-based sampling, and mixed data sources combining survey and secondary ESG reports. Further studies may also explore additional contextual factors to deepen understanding of ESG disclosure dynamics in emerging markets.

6. Conclusion

This study advances understanding of ESG disclosure in the context of Vietnamese firms by examining its key determinants and consequences within an integrated framework. The findings show that information technology systems, artificial intelligence adoption, financial capacity, managerial mindset, and regulatory frameworks positively influence ESG disclosure quality, while growth opportunity does not exert a direct effect. These results suggest that ESG disclosure quality is driven less by firms’ growth prospects and more by internal capabilities, governance orientation, and institutional pressures. Furthermore, high-quality ESG disclosure significantly enhances corporate reputation and firm performance, and corporate reputation itself serves as an important driver of performance outcomes. The results underscore that ESG disclosure is not merely a compliance activity but a strategic mechanism through which firms strengthen credibility, operational effectiveness, and long-term competitiveness in international markets.

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