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Abstract

This study examines the impact of Environmental, Social, and Governance Performance (ESGP) on profitability and firm value, focusing on 75 listed companies on the Stock Exchange of Thailand (SET) over the period 2014 to 2023. ESGP has emerged as a critical measure of corporate sustainability, yet its financial implications in emerging markets like Thailand remain underexplored. Employing the Generalized Method of Moments (GMM) approach the findings reveal that ESGP positively impacts ROA, ROE, and TBQ, emphasizing its role in enhancing operational efficiency, stakeholder trust, and market confidence. However, short- and long-term debt and cash ratio exhibit a negative impact on all financial metrics, highlighting inefficiencies linked to excessive leverage and liquidity. Firm size positively influences ROA and ROE but negatively affects TBQ, indicating challenges in market perception of growth potential for larger firms. Conversely, firm age positively impacts ROA, reflecting stability and operational experience, but presents mixed effects on ROE and TBQ due to innovation inertia and equity inefficiencies. Robustness checks using Difference GMM validate these findings, confirming the relationships between ESGP, financial metrics, and control variables. This study offers insights for corporate managers and policymakers, advocating for sustainable financial practices, optimal capital structures, and innovation-driven strategies to maximize profitability and market valuation. It contributes to the literature on sustainable finance by providing empirical evidence from an emerging market perspective and aligns with Thailand’s national sustainability agenda.

JEL Classification: G32, G34, Q56, M14, C33

Plain Language Summary

Keywords

ESG performance profitability firm value sustainability GMM

Introduction

The ability of firms to position themselves positively along the axis of Environmental, Social, and Governance (ESG) performance has become a hallmark of corporate sustainability around the world, helping guide both the strategic decisions corporations make and the investment choices of stakeholders. The performance of organizations in the arena of environmental protection, ethical behavior, and good governance (ESG performance) is now widely considered as a catalyst to long-term value generation and a potential driver of profitability (Ahmad et al., 2025; Zumente & Bistrova, 2021). Specifically, in Thailand where sustainability has emerged as a topic of significant discussion especially for listed companies on the Stock Exchange of Thailand (SET), understanding the financial impact of ESG initiatives is critical for policymakers, investors, and corporate decision-makers.

The association between ESG performance and financial results has received considerable attention, as managers concentrate on sustainable corporate behavior and its strategic consequences for companies. Well established ESG practices have been shown to facilitate operational efficiencies, risk mitigation, and increases in stakeholders trust (Chen et al., 2023), all of which lead to financial profitability and long-term market valuation. High ESG performance firms, for example, are likely to capture investors who are also focused on these attributes, and as a result, they gain better financing opportunities via enhanced credit scoring (bin Hidthiir et al., 2024; Huang et al., 2023). Furthermore, ESG initiatives can also lead to increased employee morale, customer loyalty, and regulatory compliance, all of which are beneficial for ROA and ROE (Sunitha et al., 2024).

The linkage between Environmental, Social and Governance (ESG) performance and financial performance (FP) is still under-explored in developing markets, especially in Thailand, despite some emphasis on the importance of ESG. Although several studies have provided empirical evidence that indicated a significant and positive correlation of ESG on profitability and firm value (Fahad & Busru, 2021) especially from developed economies, less empirical evidence has been published in the Thai environment, where sustainability practices are currently in their infancy as a business strategy. This gap in research creates difficulty for corporate leaders and policymakers seeking to embed ESG initiatives into business models while working within Thailand’s unique socio-economic and regulatory context.

Moreover, as many firm idiosyncratic characteristics (i.e., firm size, age, and capital structure) are positively related with the ESG performance, and also have an influence on important financial measures such as Return on Assets (ROA), Return on Equity (ROE), and Tobin’s Q (TBQ), which brings an uncertainty in determining the actual effect of ESG performance on financial behavior. Over the past decade, several studies attempted to address the dichotomy between resource-efficiency and output-efficiency, but they often fail to consider advanced moderation, thus providing limited and conflicting insights as to how firms of varying operational scale and maturity level may gain from one ESG dimension versus another (Al-Shaer et al., 2024). Moreover, if not properly adjusted for, potential endogeneity of ESG behavior and financial performance may result in biased estimates, which can undermine the findings.

The objective of this study is to analyze the effect of ESG performance on profitability (ROA and ROE) and firm value (Tobin’s Q) with a sample of 75 listed companies in the Stock Exchange of Thailand between years 2014 to 2023. By using a Generalized Method of Moments (GMM) method, this study handles possible endogeneity concerns, presenting strong evidence on the dynamic links among ESG performance, financial performance, and market valuation. The study attempts to determine the integrative factors of the relationship by adding control variables including short and long-term debt, current ratio, firm size, and age. The findings seek to enhance the emerging literature on sustainable finance, providing empirical insights from the context of an emerging market, where the link between ESG practices and firm-level financial performance remains comparatively under-researched.

The theoretical and practical implications are important, especially because business sustainability is becoming more prevalent in emerging markets, including Thailand, but remains underexamined in the literature. This research adds to the growing body of literature on sustainable finance, providing empirical evidence from a developing economy, by exploring the relationship between ESG performance and profitability (ROA and ROE) and firm value (Tobin’s Q) in a twofold manner. This is especially pertinent in the face of the growing significance of Environmental, Social and Governance (ESG) issues on the global investment and corporate agenda (Jinga, 2021).

Secondly, the paper includes firm-level attributes, such as short- and long-term debt, current ratio, size, and age as control variables to account for the subtle dynamics that drive financial performance. Such study would bring an above-average utility of the conclusions through actionable insights for the relevant engineering organization regardless of size and maturity. The findings provide useful information for policymakers, corporate leaders and investors in understanding the relationship between ESG practices, financial performance and market valuation at local level.

Thirdly, analyzing with the Generalized Method of Moments (GMM) deals with potential endogeneity issues which guarantees robustness and reliability of the results. The methodological rigor that this research possesses is what differentiates it from the rest of the pack and allows it to provide a clearer picture of the causal mechanics that exist between ESG performance and financial outcomes. The implication for corporate governance is that the ESG activities driven by ethical and reputational imperatives are also adding to long term profitability and sustainable value formation.

Finally, this study supports the reflection of Thailand’s national agenda of promoting corporate sustainability as well as the Stock Exchange of Thailand (SET)’s initiatives to promote ESG reporting and integration among listed companies. This serves not only to reinforce the implementation of ESG practices in Thailand but also to create a case study that can be adapted and adopted in other developing markets, highlighting the universal nature of sustainable financing.

Literature Review and Hypothesis Development

ESG Performance and Financial Profitability

In the past few years there has been a lot of literature and research regarding the relationship between Environmental, Social, and Governance (ESG) performance and financial profitability focusing on how sustainable companies performance translates into corporate performance. Sandberg et al. (2023) revealed that companies with higher ESG rankings generally perform better than their industry Standard, in terms of financial performance measures such as return on assets (ROA) and return on equity (ROE). They credited this outperformance to better operational efficiencies, better risk management and better relations with stakeholders. Subsequent studies support this relationship and highlight that ESG practices typically attract social investors and reduce financing costs by enhancing credit ratings (Bin Hidthir et al., 2025; Huang et al., 2023; Saliah et al., 2024).

Later meta-analyses (e.g., Friede et al., 2015), have both combined the results of more than 2,000 empirical studies, further supporting the idea that ES(I)G performance leads to financial performance. They concluded that about 90% of studies show a non-negative relationship between ESG and financial performance, and most show positive effects. The results are especially striking in developed markets where regulatory structures and investor pressures are driving sustainable behavior. In lesser-developed markets such as Thailand, the link between ESG performance and financial profitability remains significantly less understood, due in part to the immaturity of sustainability practices and confounding reporting standards.

Moreover, Thailand is an interesting context within which to study ESG performance, as companies listed on the Stock Exchange of Thailand (SET) have increasingly felt pressures from regulators and stakeholders to adopt ESG reporting frameworks. However, others point out that the costs of implementing ESG practices could outweigh the benefits, especially concerning the financial aspect of sustainability for less well-resourced or smaller firms (Amel-Zadeh & Serafeim, 2018; Cesarone et al., 2022; Hidthiir et al., 2024), even though some studies show how the inclusion of ESG principles can lead to better efficiency and risk reduction that can ultimately translate into profits. The mixed evidence indicates that new markets require region-specific background research to understand contextual nuances.

Besides, firm specific characteristics like size, age, and ownership can also affect the relationship between ESG performance and profitability. Larger corporations, for example, are likely to take more advantage of the ESG reporting system compared to smaller firms because the former have greater financial resources to invest in sustainable technologies and practices without sacrificing short-term profits (Khan et al., 2025a). Conversely, smaller firms might find it challenging to strike a balance between the costs of implementing ESG and the immediate financial returns it can possibly generate. These dynamics help underscore the need for users of empirical research to use strong methodologies like the Generalized Method of Moments (GMM) to help uncover endogeniety and truly pull apart the relationship between performance across ESG and financial results.

According to Stakeholder Theory, firms create value not only for shareholders but also for a broader set of stakeholders, including employees, customers, suppliers, regulators, and communities (Freeman, 1984). By actively engaging in ESG initiatives, firms strengthen stakeholder trust, reduce conflicts, and enhance their reputation, which translates into higher efficiency and long-term profitability. Empirical studies have shown that socially responsible firms benefit from improved employee productivity, customer loyalty, and reduced risk exposure, all of which positively influence accounting-based measures such as ROA and ROE (Eccles et al., 2014; Rahman et al., 2024). In this sense, stakeholder-oriented ESG practices serve as strategic investments that drive sustainable profitability, supporting the expectation that ESG performance enhances firm-level financial outcomes. On this basis, a working hypothesis is proposed:

H1: ESG performance has a positive impact on the profitability of firms, as measured by ROA and ROE.

ESG Performance and Firm Value

Firm value, a commonly used indicator for which Tobin’s Q is a proxy, encapsulates market expectations regarding a firm’s growth prospects, operational efficiency, and relative sustainability over time. Knoll et al. (2017) and Yang et al. (2024) also confirmed the positive effect of ESG on firm value. These advantages are supported by stakeholder theory which posits that firms pursuing the interests of multiple stakeholders (such as customers, employees, and investors) are better suited for long-term success (Freeman, 1984; Verbeke & Tung, 2013). Moreover, the resource-based view (RBV) theorizes that ESG practices are strategic resources that foster operational efficiencies and innovation and reduce risks (Abubakr et al., 2024; Saliah et al., 2023; Shirui et al., 2025; Wang et al., 2024). The discussions on theories presented support the theory of change for ESG performance leading to firm value (Hidthiir et al., 2025; Junius et al., 2020) in developed markets.

Empirical evidence also consistently suggests a positive relationship between ESG performance and Tobin’s Q (Zhou et al., 2022) concluded that firms with robust ESG practices received higher market valuations as a result of improved relationships with stakeholders and their sustainable growth potential. Also, Wu et al. (2022) and Khan et al. (2025a) found firm value increased due to material ESG factors by mitigating potential risks, and better operational efficiencies. Conversely, for nascent sustainability practices in emerging markets such as Thailand, the linkage between ESG performance and firm value remains underexplored. Although the Stock Exchange of Thailand (SET) will promote ESG compliance in listed firms through various programs, systematic studies of the financial implication of such programs are rare. This discrepancy signals the need to explore the association between ESG performance and firm value within the socio-economic context of Thailand.

While overall the relationship between ESG performance and firm value is positive, some moderating factors can affect this relationship. Certain firm-specific features such as size, age or financial structure is key. It stands to reason that larger firms derive greater benefits from ESG initiatives as they have more resources and processes in place, while smaller firms may face resource restrictions (Ali et al., 2025; Drempetic et al., 2020; Khan et al., 2025b).

From the perspective of Signaling Theory, firms use ESG practices to send credible signals of quality, transparency, and long-term commitment to the market (Spence, 1973). High ESG performance communicates to investors that the firm effectively manages environmental and social risks while maintaining strong governance, thereby reducing information asymmetry and perceived investment risk. This enhanced credibility can attract socially responsible investors, improve access to capital, and strengthen market confidence, which are directly reflected in higher market-based valuations such as Tobin’s Q. Prior studies confirm that ESG leaders often enjoy superior investor recognition and valuation premiums, suggesting that ESG acts as a positive signal of sustainable value creation (Fatemi et al., 2018; Isa et al., 2025). Also, industry dynamics and regulatory landscape can further enhance or erode the benefits of ESG practices. These moderating factors are particularly relevant within Thailand as regulatory frameworks and investor awareness of ESG principles are still developing. Thus, this research will fill in the gap by investigating the hypothesis:

H2: ESG performance positively affects firm value, as measured by Tobin’s Q.

Methodology

Sample and Data Collection

The sample used for this study was selected from the Thailand Stock Exchange, where 75 publicly listed firms are included based on their availability to explore the impact of ESG performance to business performance as described by ROA, ROE, and TBQ. The secondary data needed for the econometric analysis was obtained from Bloomberg (2023) for the period 2014 to 2023. To improve data reliability, data cleaning is a pre-processing step in which missing or incomplete data is treated with interpolation and extrapolation methods. The 10-year time frame was selected because it would encompass appropriate trends and patterns, facilitating analysis of the firms’ ESG performance and financial performance over a long-term horizon. Bloomberg was chosen as the primary data source. In contrast to many other databases that only show binary information regarding an entity’s ESG performance, Bloomberg provides actual ESG scores on a well-grounded range from 0 to 100. These are based on 120 indicators covering environmental, social and governance dimensions to provide a nuanced, quantitative assessment of ESG performance. Vicinity data is well-grounded in the local context and introduces a high degree of relevant granularity along the value chain.

Variables and Measures

Dependent Variables

Return on Assets (ROA), a common causal measure of firm-level profitability, calculated as earnings before interest as a function of total assets. The efficiency of a firm in using assets to produce profits per unit of production serves as an important indicator of operational performance (Delmas et al., 2015). Return on Equity (ROE) is another measurement similar to ROI it describes a business profitability in relation to shareholders equity. ROE is especially a useful metric when it comes to forecasting stock returns and the long term financial condition of a firm, and reflecting how well management is using shareholder investments to yield earnings (DeGeorge et al., 2013; Eugene & French, 1992). Tobin’s Q is also used as a financial performance indicator alongside ROA and ROE. Tobin’s Q evaluates the relationship between a company’s market valuation and the replacement cost of its assets, providing insight into capital investment efficiency and market evaluations of growth potential. Tobin’s Q greater than 1, in general, represents firm good investments, showing that market value is greater than the cost of replacing assets (Hejazi et al., 2016; Mysaka et al., 2021). Cumulatively, these three measures—ROA, ROE, and Tobin’s Q—capture an essential assessment of FP from operational, equity, and market viewpoints. Consequently, this study employs ROA, ROE, and Tobin’s Q as reference factors for assessing financial performance. Table 1 provides a detailed description of the variables involved and how they were measured, assuring clarity and reproducibility of the study’s methodology.

Table1.

Variable Description.

Category	Variable	Measurement	Expected result
Dependent variables	ROA	Return on assets = net profit after tax/total assets	−/+
	ROE	Return on equity = net profit after tax/equity capital	−/+
	TBQ	Tobin’s Q = market value of assets/replacement cost of capital	−/+
Independent variables	ESG performance	ESG performance = calculated from a total of 120 indicators (ranges from 1 to 100)	−/+
Control variables	AGE	AGE = natural log of age of firm from the date of incorporation	−/+
	SALTD	SALTD = short and long-term debt	−/+
	CR	CR = cash ratio	−/+
	LSIZE	LSIZE = log (total assets)	−/+

Independent Variables

Companies are evaluated on a scale from 1 to 100 based on their performance on 120 indicators focusing on environmental, social and governance performance. This overall indicator measures the performance of a company in three key areas: environmental accountability, social impact, and governance (Bloomberg, 2023). This is because, according to Eric et al. (2022), solid ESG metrics allow companies to be proactive in their risk recognition and management, while seizing opportunities that can be focused on in the long run to create value. This holistic methodology guarantees the accuracy of ESG scores, producing a reliable barometer for investors, regulators, and other interested parties seeking an assessment of a firm’s commitment to sustainable and responsible corporate practices.

Control Variables

To control for firm-level features that could affect financial and ESG performance, this study includes several control variables. Firm age (AGE) is defined as the natural logarithm of the number of years since the firm was incorporated and captures the stability and experience in operations of the firm, which may positively affect its ability to adopt sustainable practices and increase profit (Coad et al., 2018). Short- and long-term debt (SALTD) reflects financial leverage of the firm, and moderate levels of debt tend to promote its financial performance through efficient allocation of capital (Myers, 1977). Cash ratio (CR) is a metric calculated by dividing cash and cash equivalents by current liabilities; CR provides a measure of liquidity and financial flexibility, both of which can facilitate efforts in ESG investing and operational efficiency (Nguyen et al., 2016). Firm Size (LSIZE): The size of a firm is measured by the natural logarithm of its total assets (Dang et al., 2018), which is significant in the context of our research due to these perceived advantages—Economies of scale, and more significant regulatory and stakeholder scrutiny, benefit larger firms, which in turn positively affect both financial performance and ESG compliance.

Model Specification and Analytical Techniques

The study is aimed at examining the result of Environmental, Social and Governance (ESG) performance on profitability and firm value of the 75 listed companies on the Thailand Stock Exchange of ultimate stock from 2014 to 2023. The study performs Generalized Method of Moments (GMM) estimation technique to deal with concern of endogeneity and obtain robust results. In particular, it employs the system GMM estimator, which allows us to take into consideration the within-differences of variables, which helps control for problems like heterogeneity, heteroscedasticity, autocorrelation, and endogeny that ordinary panel estimators such as Ordinary Least Squares (OLS), Random Effects (RE) and Fixed Effects (FE) do not (Arellano & Bond, 1991). The study also includes the difference GMM approach to further validate the robustness of findings. Arellano-Bond difference GMM estimator uses first differenced variables to eliminate unobserved time-invariant heterogeneity and reduce bias from omitted variables. One way to solve the problem of controlling endogeneity is the use of lagged values of dependent and independent variables as instruments, an approach that has proved to explain better the relationships. The differencing eliminates or reduces potential problems related to autocorrelation and heteroscedasticity, both of which are common in panel data (Arellano & Bond, 1991).

In this study, the Generalized Method of Moments (GMM) is employed instead of traditional methods such as OLS, Fixed Effects, or Random Effects due to its ability to address key econometric challenges inherent in the ESGP–firm performance relationship. ESGP and financial outcomes are likely endogenous, as profitable firms may invest more in ESG while ESG practices can, in turn, enhance profitability. Moreover, profitability and firm value are dynamic processes influenced by their past values, which conventional estimators cannot capture without bias. GMM effectively controls for endogeneity, simultaneity, and unobserved firm-specific heterogeneity by using internal instruments and lagged variables, ensuring consistent estimates even under heteroskedasticity and autocorrelation. While limitations such as instrument proliferation and finite sample bias exist, careful specification and robustness checks (Difference GMM) validate the findings, making GMM the most suitable approach for this panel data study.

The difference GMM method can be justified since it complements the system GMM estimator. Therefore, although system GMM constructs both level and difference equations to increase efficiency, the difference GMM estimator uses first differences exclusively, which provides a more rigorous control for unobserved heterogeneity and thus a robustness check with respect to the validity of the instruments (Blundell & Bond, 1998). Prior research has indicated that the best practices in these studies was to perform multiple approaches to confirming results, as that it provides more reliable results, especially in persistent dependent variable datasets, as is often the case in financial performance metrics (Roodman, 2009). The utilization of difference GMM in the analysis further strengthens the results, helping to ensure that they are robust to potential biases that may exist in dynamic panel models.

This study employs the Difference GMM estimator alongside the main System GMM model to verify the consistency and stability of results. Difference GMM, introduced by Arellano and Bond (1991), transforms variables into first differences to remove unobserved firm-specific effects and control for endogeneity using lagged instruments. Its use ensures that the findings are not driven by the assumptions or potential instrument proliferation of the System GMM. Alternative estimators such as OLS or fixed effects would yield biased results in dynamic settings with endogenous regressors. Therefore, Difference GMM provides a methodologically coherent and reliable robustness test for dynamic panel data analysis.

The study structural equation is given as follows:

R O A_{i t c} = a_{0} * β_{1} R O A_{i t c - 1} * β_{2} E S G P_{i t c} * β_{3} S A L T D_{i t c} * β_{4} C R_{i t c} * β_{5} L S I Z E_{i t c} * β_{6} A G E_{i t c} * ε_{i t c}

(1)

RO E_{itc} = a_{0} + β_{1} RO E_{itc - 1} + β_{2} ESG P_{itc} + β_{3} SALT D_{itc} + β_{4} C R_{itc} + β_{5} LSIZ E_{itc} + β_{6} AG E_{itc} + ε_{itc}

(2)

TB Q_{itc} = a_{0} + β_{1} TB Q_{itc - 1} + β_{2} ESG P_{itc} + β_{3} SALT D_{itc} + β_{4} C R_{itc} + β_{5} LSIZ E_{itc} + β_{6} AG E_{itc} + ε_{itc}

(3)

In the above models, α₀ stands for intercept, i represents the firm, t stands for the time, c stands for the country. ROA_itc−1 is the one period lagged for the dependent variable. ε indicates the error term in the models.

Estimation based on the model may encounter three sources of endogeneity: simultaneity, arising when the independent variables operate both as functions and as the expected values of the dependent variable; unobservable heterogeneity, where factors not directly observable are influenced by both the dependent and explanatory variables. Measurement error occurs when there are inaccuracies in the measurement of variables, which can bias the estimated relationships in the model. To address these challenges, the GMM estimator is employed, following the approach outlined by Blundell and Bond (1998). This choice finds support in the work of Li (2016), who postulated that GMM exhibits the most robust correction impact on coefficients.

Result and Discussion

The descriptive statistics in Table 2 provide insights into the characteristics of the variables analyzed. The ESGP has 750 observations, with a mean score of 53.942 and a standard deviation of 18.88, indicating moderate variability in ESG performance. The minimum ESGP value is 0, and the maximum is 83.221, highlighting a wide range of performance among entities.

Table 2.

Descriptive Statistics.

Variable	Obs.	Mean	SD	Min	Max
ESGP	750	53.942	18.88	0	83.221
ROE	750	20.871	16.992	−49.348	105.867
ROA	750	7.568	6.275	−6.945	30.232
TBQ	750	2.554	1.865	0	11.775
SALTD	750	121,112.45	181,542.86	0	1,193,593.7
CR	750	1.7	1.266	0	10.373
LSIZE	750	13.395	1.472	9.016	17.209
AGE	750	19.7	9.103	1	38

Return on Equity (ROE) and Return on Assets (ROA) are key indicators of financial performance. ROE has a mean value of 20.871 with a standard deviation of 16.992, reflecting substantial variability across observations. Its range ranges from −49.348 to 105.867, indicating that while some firms have negative equity returns, others have significantly high performance. ROA has a mean of 7.568 and a standard deviation of 6.275, with values ranging from −6.945 to 30.232, suggesting relatively lower variability compared to ROE. Furthermore, the Tobin’s Q (TBQ), a measure of market valuation, averages 2.554 with a standard deviation of 1.865. The range, from 0 to 11.775, indicates variation in firms’ market valuations. SALTD, with a mean of 121,112.45 and a standard deviation of 181,542.86, demonstrates substantial variability in firm sales, ranging from 0 to a maximum of 1,193,593.7.

Moreover, Current Ratio (CR), a liquidity measure, has a mean of 1.7 and a standard deviation of 1.266, with a range from 0 to 10.373, showing that most firms maintain moderate liquidity levels. LSIZE averages 13.395 with a standard deviation of 1.472, ranging from 9.016 to 17.209, reflecting variation in firm sizes. Lastly, Firm Age (AGE) has a mean of 19.7 years with a standard deviation of 9.103, indicating that the sample comprises both relatively new and well-established firms, with ages ranging from 1 to 38 years.

The correlation analysis in Table 3 examines the relationships between ESGP and other key variables, including SALTD, CR, LSIZE, and AGE. The findings reveal a positive correlation between ESGP and SALTD (0.276), suggesting that firms with higher ESG performance tend to have higher levels of short and long-term debt. Similarly, ESGP shows weak positive correlations with LSIZE (0.101) and AGE (0.082), indicating that larger and older firms may slightly outperform in ESG metrics. Conversely, ESGP is negatively correlated with CR (−0.103), implying that firms with higher ESG scores may maintain lower liquidity ratios.

Table 3.

Matrix of Correlations.

Variables	ESGP	SALTD	CR	LSIZE	AGE
ESGP	1.000
SALTD	0.276	1.000
CR	−0.103	−0.214	1.000
LSIZE	0.101	0.100	−0.101	1.000
AGE	0.082	0.026	−0.213	0.152	1.000

Furthermore, SALTD exhibits a negative correlation with CR (−0.214), indicating that firms with higher debt levels tend to have reduced liquidity. A weak positive correlation between SALTD and LSIZE (0.100) suggests that larger firms are more likely to carry higher levels of debt, while its negligible correlation with AGE (0.026) indicates no significant association with firm age. CR shows negative correlations with both LSIZE (−0.101) and AGE (−0.213), suggesting that larger and older firms tend to operate with lower liquidity levels, potentially reflecting strategic financial management decisions.

Finally, LSIZE demonstrates a weak positive correlation with AGE (0.152), suggesting a slight tendency for larger firms to be older. LSIZE’s modest correlations with ESGP (0.101) and SALTD (0.100) indicate its limited influence on ESG performance and debt levels. AGE shows a weak positive correlation with ESGP (0.082) but negligible relationships with other variables, suggesting its minimal direct impact on financial metrics.

As shown in the GMM results in Table 4, the prefix “L.” is used to denote lagged variables in the econometric analysis. A lagged variable represents the value of a variable from a previous time period, typically used to capture dynamic relationships and temporal dependencies within the data. For instance, L.ROA, L.ROE, or L.TBQ indicate the one-period lag of Return on Assets, Return on Equity, and Tobin’s Q, respectively. Including lagged terms in time-series or panel data models helps account for persistence effects, where the current performance or outcome depends partly on past performance.

Table 4.

Regression Result of System GMM.

Variables	ROA	ROE	TBQ
L.	0.598*** (0.00254)	0.642*** (0.00370)	0.662*** (0.00129)
ESGP	0.0348*** (0.00412)	0.0248* (0.0142)	0.0271*** (0.000247)
SALTD	−1.0805*** (6.2507)	−9.0106*** (7.4807)	−1.2906*** (5.9508)
CR	−0.502*** (0.0204)	−2.842*** (0.149)	0.0395*** (0.00172)
LSIZE	0.490*** (0.0154)	1.726*** (0.0557)	−0.0316*** (0.00131)
AGE	0.101*** (0.00622)	−0.341*** (0.0286)	−0.0237*** (0.000351)
Hansan/Sargan	0.1129	0.1181	0.1137
AR (1)	0.2195	0.1950	0.1523
AR (2)	0.0987	0.1189	0.1421
Number of instruments	47	47	47
Observations	750	750	750
Number of companies	75	75	75

Note. Standard errors in parentheses.

p < .1. **p < .05. ***p < .01.

The lagged values of ROA, ROE, and TBQ have a significant positive effect on their values in the present. This result demonstrates that we observe a carryover of these variables over time (i.e., past performance and market valuation are strongly positive determinants of current financial performance and firm value). Confidence that strengthens returns and is rooted, in the past, the high ROA and ROE show the possibility of operational stability and strategic management of firms, therefore, providing sustainability for the future, and the indicator of the TBQ in the previous period indicates that investments are being efficient and are likely to influence the growth of the company, which generates investor confidence.

By contrast, the third finding, where Environmental, Social, and Governance Performance (ESGP) positively affects ROA, ROE, and TBQ, means firms with strong ESG practices enjoy higher profitability and market valuation. In particular, the positive correlation with ROA indicates that ESG-focused firms allocate resources more effectively, leading to higher profit levels than can be attributed to their asset base. Concurrently, the encouraging appraisement of ROE shows that these companies yield bigger earners for its shareholders, possible because of its operational efficiencies, better stakeholder confidence & less risks. A significant positive relationship with TBQ indicates that the market prices firms with good ESG compliance higher compared to others; these firms are expected to be sustainable, well-governed and less susceptible to either reputation risk or regulation risk. These finding are in congruence to the study of Eccles et al. (2014), so companies committed to sustainability practices outperform competitors on profit and market value due to operational efficiencies and stakeholder relations. Similarly, Friede et al. (2015), in a meta-analysis of over 2,000 studies, report that the vast majority of studies find that ESG performance is positively associated with financial performance. Khan et al. (2025b) pointed to material ESG practices—those most salient to a firm based on its industry as especially capable of improving financial and market measures.

Also, the negative effect of short- and long-term debt (SALTD) on ROA, ROE, and TBQ put a bright-light on the high levels of leverage providing an inhospitable environment for the profitability and the market valuation of a company. More specifically, the negative relationship with ROA suggests that a higher debt burden leads firms to generate less profit per dollar of assets, with high-interest repayments and obligations likely to be the reason for their inefficiency. The negative impact on ROE indicates that excessive debt undermines returns to shareholders, as debt-servicing costs erode net income. Similarly, the negative relationship with TBQ suggests that the market perceives high leverage as a risk factor, leading to lower valuations relative to the firm’s assets. The finding aligns with the study of Myers (1977) who assumed in the trade-off theory of capital structure that while debt can provide tax shields, excessive leverage increases financial distress costs, ultimately outweighing its benefits. Similarly, Rajan and Zingales (1995) demonstrated that high debt levels are negatively associated with firm profitability due to the increased burden of fixed financial obligations. More recent studies, such as those by Jensen and Meckling (1976), emphasize that high leverage can exacerbate agency conflicts between creditors and shareholders, further eroding firm value.

The result indicating that Cash Ratio (CR) has a negative impact on ROA and ROE but a positive impact on TBQ suggests a nuanced relationship between liquidity management and financial outcomes. A negative impact on ROA and ROE implies that holding excessive cash reduces a firm’s profitability, as idle cash may not be utilized effectively to generate returns. High liquidity levels can indicate underutilized resources, reflecting inefficiencies in asset allocation and investment strategies. Conversely, the positive relationship with TBQ indicates that the market views higher cash reserves as a signal of financial stability and the ability to invest in future growth opportunities, thus increasing the firm’s market valuation. This result is similar with the study of Ferreira and Vilela (2004) it shows that while maintaining high cash reserves enhances financial flexibility and reduces the risk of financial distress, excessive liquidity can lead to inefficiencies and agency problems, where managers may hoard cash or fail to deploy it in value-generating investments. Jensen (1986) highlighted in his free cash flow hypothesis that excessive cash holdings could exacerbate agency conflicts, as managers may engage in suboptimal projects instead of returning value to shareholders. Similarly, Dittmar and Mahrt-Smith (2007) demonstrated that cash reserves are valued positively by markets (as reflected in TBQ) but can negatively impact profitability metrics like ROA and ROE due to underperformance in resource allocation.

The negative effects of short- and long-term debt and the cash ratio on firm performance may not be uniform across all industries in Thailand, reflecting sectoral heterogeneity in capital structure needs and liquidity management. For instance, capital-intensive sectors such as energy, real estate, and infrastructure often rely heavily on long-term debt to finance large projects, where leverage can enhance growth potential rather than undermine profitability. Conversely, service-oriented or technology-based firms may face efficiency losses from excessive borrowing, as high leverage signals financial fragility and constrains innovation. Similarly, while maintaining high cash reserves may reduce agency costs in financial institutions by improving liquidity buffers, in consumer goods or retail sectors it can reflect underutilized resources, leading investors to interpret it as inefficiency. These variations suggest that the observed negative impact of debt and cash ratio may be more pronounced in certain industries, emphasizing the need to contextualize ESG–finance linkages within Thailand’s sectoral dynamics.

The result indicating that firm size has a positive impact on ROA and ROE but a negative impact on TBQ suggests that larger firms benefit from operational efficiencies and resource utilization that enhance profitability, but their market valuation relative to assets may decline. The positive impact on ROA and ROE implies that larger firms can leverage economies of scale, reduce per-unit costs, and achieve greater operational stability, resulting in higher profitability. However, the negative relationship with TBQ indicates that the market may perceive larger firms as having lower growth potential or greater inefficiencies in deploying their assets for future value creation. Altuntas et al. (2021) have similar results with Ahmad et al. (2024), it illustrates the fact that larger firms tend to enjoy operational economies of scale and less risk exposure which contribute to improved profitability expressed as ROA and ROE. Yet, according to Demsetz and Villalonga (2001), structural weaknesses including bureaucratic inertia, low flexibility, and reduced innovative capacity typically attenuate growth openings and market appraisal (evidenced by TBQ) with company size. In a similar light, Singh and Whittington (1975) viewed larger firms that display stable profits as less favorable due to their relative inflexibility and absence of dynamism needed for high market valuations in comparison to their assets.

The outcome showing a positive effect of age on ROA and a negative effect on ROE and TBQ implies that as firms age, they develop operational experience and stability, which improves their ability to yield returns on assets, although they struggle with efficiency of equity return and market valuation. The incremental benefit in ROA suggests that mature firms use their experience, established procedures, and market reputation to use assets to generate profits. In contrast, a fall in ROE can certainly represent diminishing marginal returns on equity brought on by less aggressive financial policies or bottlenecks that are common to older companies. You are tuned to data until October 2023. This result is in line with Rahman et al. (2024) and Coad et al. (2018), older firms tend to be more stable and organized than their younger counterparts, resulting in better profitability ratios such as ROA. However, Jensen and Meckling (1976) indicated that in older firms, the management increasingly tends to assume conservative financial policies that exclude maximizing returns of equity. Furthermore, Majumdar (1997) provided evidence that older firms suffer from bureaucracy and reduced flexibility, which results in diminishing growth opportunities and lower market valuations, in accordance with the negative age-TBQ relationship.

Economically, ESG initiatives improve financial outcomes through multiple mechanisms: strong environmental practices enhance operational efficiency by reducing waste, conserving energy, and optimizing resource use, which lowers costs and improves margins; robust social engagement fosters stakeholder trust, leading to stronger employee commitment, customer loyalty, and better community relations that reduce reputational risks and transaction costs; and sound governance strengthens market confidence by improving transparency, reducing agency problems, and signaling long-term sustainability to investors. These mechanisms collectively translate ESGP into higher profitability (ROA and ROE) and improved market valuation (Tobin’s Q). Since these relationships are potentially bi-directional profitable firms may also allocate more resources to ESG GMM provides consistent estimates by using lagged instruments to capture dynamic effects, with robustness checks via Difference GMM validating the results.

The Hansen and Sargan tests are diagnostic tools used in Generalized Method of Moments (GMM) estimation to assess the validity of the instruments employed in the model. These tests examine whether the instruments are appropriately uncorrelated with the error term—an essential condition for consistent estimation. A non-significant p-value (p > .05) for either test supports the null hypothesis that the instruments are valid, meaning they are exogenous and correctly specified. Conversely, a significant p-value (p < .05) may indicate potential problems with the instrument validity, suggesting that some instruments might be correlated with the error term or that the model is over-identified. Therefore, in the results presented in Tables 4 and 5, non-significant Hansen or Sargan test p-values confirm that the selected instruments are appropriate and that the model satisfies the required orthogonality conditions.

Table 5.

Robustness Result of Difference GMM.

Variables	ROA	ROE	TBQ
L.	0.496*** (0.00652)	0.560*** (0.00492)	0.392*** (0.00394)
ESGDP	−0.132*** (0.0126)	0.428*** (0.0279)	0.00999*** (0.00111)
SALTD	−1.2905*** (1.2106)	−2.8305*** (1.5206)	−1.7906*** (1.8007)
CR	−0.586*** (0.0510)	−3.337*** (0.240)	−0.103*** (0.00446)
LSIZE	0.205* (0.109)	−3.121*** (0.883)	−0.200*** (0.0283)
AGE	0.289*** (0.0236)	0.957*** (0.0850)	0.0291*** (0.00236)
Hansan/Sargan	0.1908	0.1301	0.1501
AR (1)	0.2087	0.1381	0.1054
AR (2)	0.1216	0.0731	0.1536
Number of instruments	52	52	52
Observations	750	750	750
Number of companies	75	75	75

Note. Standard errors in parentheses.

p < .1. **p < .05. ***p < .01.

Robustness Result

In the context of this study, Table 5 shows the robustness results obtained from Difference GMM which confirm the consistency of the findings related to the relationship between ESG performance (ESGP), financial profitability (ROE), and firm value (Tobin’s Q). By focusing on the first differences of the variables, this method eliminates unobserved time-invariant heterogeneity, ensuring that the relationships identified are genuine and not driven by unobserved factors or reverse causality. For instance, the robustness results reaffirm the positive impact of ESGP on ROE as well as Tobin’s Q, while also validating the observed effects of control variables like firm size, age, and liquidity on financial outcomes where SALTD negatively affects ROA, ROE, and TBQ, highlighting the risks of excessive leverage. High debt levels increase financial obligations, reducing profitability and market valuation, as also noted by Myers (1977) in the trade-off theory of capital structure. Similarly, the CR exhibits a negative impact on all three metrics, highlighting the inefficiencies of excessive liquidity. These results resonate with Jensen’s (1986) free cash flow hypothesis, which posits that idle cash may lead to suboptimal investments, negatively affecting financial outcomes. In contrast, firm size is positively related to ROA (thus indicating operational efficiencies and economies of scale) but negatively relates to ROE (which indicates decreased profitability on wider asset bases) and TBQ. According to this finding, larger firms may suffer from higher bureaucratic ineptitude and from slower growth potential, in line with findings of Demsetz and Villalonga (2001).

In contrary, firm age has positive effect on ROA, ROE and TBQ, which suggests that newer firms gain less from operational experience, established reputations and market stability than older firms. As a result, mature firms tend to deliver stable returns on assets and equity, along with attractive market multiples. This finding is consistent with those of Coad et al. (2018), which recognize age is a factor of financial security and effectiveness.

The contrasting results between Difference GMM and System GMM regarding the effect of ESG performance (ESGP) on ROA highlight important methodological and contextual considerations. Difference GMM, which relies on first-differenced instruments, often suffers from weak instrumentation in small or moderately sized samples, potentially producing biased or inconsistent estimates (Roodman, 2009). This can explain why ESGP appears to negatively affect ROA in the Difference GMM estimation, as the loss of information from differencing may amplify noise relative to signal. In contrast, System GMM combines equations in levels and differences, improving efficiency and addressing weak instrument problems, making its results generally more reliable for dynamic panel models. The positive relationship observed in System GMM thus better reflects the theoretical expectation that ESG initiatives enhance resource efficiency, stakeholder confidence, and firm reputation, ultimately boosting profitability. The discrepancy underscores the importance of robustness checks across estimation methods and suggests that while ESGP’s short-term accounting returns (captured in ROA under Difference GMM) may sometimes be burdened by upfront costs of sustainability investments, the broader evidence from System GMM supports a net positive effect on profitability in the Thai context.

Furthermore, the extent to which companies benefit from ESG practices is not uniform, but rather conditioned by firm characteristics and industry dynamics. Larger firms often benefit more from ESG initiatives because they face greater visibility and scrutiny from investors, regulators, and the public; hence, their ESG investments more effectively translate into improved reputation, stakeholder trust, and access to capital. However, market perceptions may also penalize larger firms if their growth potential is seen as limited, which can weaken valuation measures such as Tobin’s Q. Older firms tend to leverage ESG practices to signal stability, operational resilience, and commitment to long-term sustainability, which can enhance profitability yet, they may face challenges such as innovation inertia or entrenched governance structures, reducing the efficiency of ESG initiatives in driving equity returns. Industry-specific factors also play a critical role: companies in resource-intensive sectors like energy, manufacturing derive direct cost savings and regulatory compliance benefits from environmental initiatives, while firms in consumer-facing industries like retail, services gain more from social and governance dimensions, as customers and investors increasingly reward firms demonstrating ethical practices and transparency. Thus, the financial impact of ESGP is shaped not only by the quality of initiatives but also by firm size, age, and industry context, underscoring the heterogeneity in outcomes across the corporate landscape.

Moreover, in the Thai context, the mechanisms linking ESG performance to financial outcomes operate through three reinforcing channels: operational efficiency, risk mitigation, and capital market signaling. First, ESG investments in energy efficiency, waste reduction, and climate resilience directly enhance operational performance and reduce input volatility. For example, several large Thai firms, including PTTEP and leading property developers, have aligned their sustainability strategies with the Task Force on Climate-related Financial Disclosures (TCFD) framework, integrating energy efficiency and transition risk management into core operations, which supports improved profitability measures such as ROA and ROE (Stock Exchange of Thailand [SET], 2023a; International Financial Reporting Standards [IFRS], 2023). Second, ESG practices strengthen risk management and stakeholder trust. The Thai Collective Action Coalition Against Corruption (CAC) has become a key governance initiative, with listed firms across industries (e.g., seafood, retail, and energy) obtaining certification to reduce corruption risk, enhance reputational capital, and improve cash flow stability (CAC, 2023; Transparency International, 2022). Such initiatives lower regulatory and reputational costs, positively impacting firm profitability. Third, ESG activities act as signals in capital markets. The introduction of the SET ESG Ratings (formerly THSI) and the creation of the SET ESG Index provide visible benchmarks for investors. Empirical evidence shows that Thai firms with higher ESG ratings enjoy valuation premiums, stronger investor recognition, and lower financing constraints, all reflected in Tobin’s Q (SET, 2023b; Wattanatorn & Kleinhans, 2024). These mechanisms are reinforced by regulatory developments, including the Securities and Exchange Commission (SEC) Thailand’s adoption of IFRS S1/S2 sustainability disclosure standards and the phased rollout of the Thailand Green Taxonomy (Phase II, Bank of Thailand, 2024), which defines sector-specific emission thresholds (e.g., power sector capped at 100 gCO₂e/kWh) and channels cheaper credit toward compliant firms (Bank of Thailand, 2024; Ministry of Finance, 2023). Sector-specific dynamics further shape these effects: energy and heavy industry firms benefit most from efficiency and compliance-driven cost savings, consumer-facing and tourism firms gain from stronger governance and social responsibility enhancing brand equity, and export-oriented agribusiness strengthens competitiveness through supply chain compliance with international ESG standards.

In addition to this, the positive relationship between ESG performance and financial indicators such as ROA, ROE, and Tobin’s Q suggests that companies adopting robust ESG practices not only fulfill social and environmental obligations but also achieve superior financial outcomes. In practical terms, firms that integrate ESG principles into their strategic and operational decisions can reduce risk exposure, attract long-term capital, and enhance their market reputation—key drivers of sustainable competitiveness. Managers can utilize these insights to align corporate strategies with sustainability frameworks, optimize resource allocation, and build stakeholder trust, which ultimately translates into cost savings and improved productivity. Meanwhile, the negative effects of high leverage and excess liquidity provide managers with evidence to maintain an optimal capital structure and efficient cash management policies to prevent value erosion. These results offer actionable guidance for corporate leaders to strengthen governance, improve financial discipline, and leverage ESG initiatives as a strategic tool for long-term profitability and resilience in Thailand’s evolving business landscape.

Policy Implications

This study’s research results confirmed that ESGP constitutes vital impacts for publicly held firms involving SET. The effect of ESGP on ROA, ROE, and TBQ with positive coefficients suggests that ESGP can improve profitability, shareholder returns, and market valuation. Well-designed ESG practices lead to operational efficiency, stakeholder trust, and better reputation for firms, so they become sustainable and well-governed companies. To capitalize on these benefits, companies must embed ESG principles into their strategic frameworks, focusing on the material ESG factors that are most pertinent to their industries. Tax incentives, grants, and mandatory ESG disclosures can enhance ESG compliance.

Short-term and long-term debt had negative effects on ROA, ROE, and TBQ, which indicates the extreme risk of over-leverage. According to Myers’ (1977) trade-off theory of capital structure, high levels of debt create financial obligations that decrease profitability and negatively impact market valuation. Meanwhile, companies will need to adopt a balanced capital structure by optimizing their debt-to-equity ratios, cutting their reliance on costly borrowing, and utilizing resources wisely. Policymakers can facilitate these actions by fostering access to affordable credit for companies with good governance. Findings from the cash ratio (CR) are somewhat similar, though—excessive liquidity simultaneously inhibits profitability in line with the economic theory; however, it has a positive movement on the market valuation due to signaling financial stability. According to Ferreira and Vilela (2004), in order for companies to improve the efficiency of their operations, organizations must balance liquidity by reinvesting current cash that has not been associated with any projects to improve organizational efficiencies or disbursing surplus funds to shareholders.

The variation in financial performance is shaped by postulants including firm size and age. Size creates economies of scale such that larger ROA and ROE are paired with declining TBQ due to inefficiency or limiting growth perceptions. Older firms, likewise, demonstrate a strong ROA consistent with stability and operational experience but low ROE and TBQ suggests conservative financial policies and a decreased ability to innovate. For large and mature firms, managers should emphasis on modernizing operations, innovation, and agility to maintain market competitiveness. Policymakers could encourage R&D initiatives and facilitate digital transformation of such firms to overcome structural issues and sustain market relevance.

Regulators such as the SEC and SET should accelerate mandatory adoption of IFRS S1/S2 standards to improve disclosure quality, while expanding the SET ESG Ratings and SETESG Index to incentivize better practices. The recently launched Thailand Taxonomy should be operationalized in bank lending and investment decisions to channel capital toward green and sustainable activities, while anti-corruption and governance initiatives like CAC certification should be integrated into ESG assessments to strengthen investor trust. Targeted green financing schemes, such as concessional loans and green bonds, can reduce the cost of ESG investments, especially for SMEs, while sector-specific requirements (e.g., emission thresholds for energy and manufacturing) ensure focused impact. Together, these measures align with Thailand’s 2023–2025 sustainability roadmap and provide a framework to enhance profitability, firm value, and long-term market confidence.

The findings demonstrate that Environmental, Social, and Governance Performance (ESGP) has strong economic significance for listed firms on the SET, as it enhances profitability (ROA, ROE) and market valuation (TBQ). This confirms that ESG engagement is not merely ethical compliance but a strategic investment that improves efficiency, investor confidence, and firm reputation. Conversely, high short- and long-term debt reduce profitability and value, emphasizing the risks of excessive leverage, while excessive liquidity also constrains returns despite signaling financial stability. The mixed effects of firm size and age reveal that although larger and older firms gain from economies of scale and experience, they may face innovation inertia and lower market expectations. Overall, the results highlight that integrating ESG principles with balanced financial management creates sustainable competitive advantage and long-term firm value in Thailand’s evolving corporate landscape.

Conclusion and Future Research

The research provides insights concerning the sustainability of performance (Environmental, Social and Governance Performance), profitability and value of corporate firms among 75 listed companies on SET during 2014–2023. Following the GMM methodology, the results demonstrate that ESGP is associated with an increase in profitability (as measured by ROA and ROE) and improved market valuation (TBQ). Firm specific characteristics play a central role in determining the overall outcomes. Short- and long-term debt and cash ratio have a negative influence on profitability (ROA, ROE) and market value (TBQ), indicating inefficiencies related to high levels of leverage and liquidity. Firm size has been found to positively influence ROA and ROE, as larger firms may benefit from operational efficiencies and economies of scale, but negatively influence TBQ, indicating that larger firms may face challenges regarding their growth potential and market perception. Likewise, firm age has a significant positive effect on ROA, due to operational expertise and stability, while negative declarations on ROE and TBQ highlight issues of equity efficiency and innovation inertia mark mixed contribution on ROE and TBQ. Using Difference GMM, these findings are robust and are consistent with regards to ESGP, financial indicators and control variables (firm size, age and liquidity). The findings of this research contribute to the field by offering pragmatic policy alternatives for corporate managers and regulators alike, elucidating the significance of sustainable financial practices, efficient capital allocation, and innovative designs that reconcile near-term operational efficiencies with longer-term market expectations. By integrating ESG principles and addressing financial inefficiencies, firms can enhance profitability and value creation while contributing to sustainable development. The limitations of this are, firstly, the sample is limited to 75 SET-listed firms, which may constrain generalizability to unlisted firms, SMEs, or other ASEAN markets. Secondly, ESGP is treated as an aggregate indicator; the analysis cannot fully disentangle which E, S, or G pillars drive profitability and valuation effects. Thirdly, despite using System and Difference GMM, residual endogeneity and measurement error in ESGP and accounting variables may persist. Future research can explore sector-specific ESG impacts, incorporate macroeconomic variables, analyze long-term and cross-country effects, investigate behavioral dynamics, assess the role of digital transformation in ESG implementation, and examine the relationship between control variables, financial risks, and ESG practices for deeper insights.

Footnotes

ORCID iDs

Ahmed Mahade

Zaki Ahmad

Ethical Considerations

There are no human participants in this article and informed consent is not required.

Consent to Participate

This article does not contain any studies with human participants or animals.

Consent for Publication

This manuscript does not contain any individual person’s data in any form.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

All the data and materials are available on reasonable request from the corresponding author.*

References

Abubakr

A. A. M.

Khan

Mohammed

A. A. A.

Abdalla

Y. A.

Mohammed

A. A. A.

Ahmad

(2024). Impact of AI applications on corporate financial reporting quality: Evidence from UAE corporations. Qubahan Academic Journal, 4(3), 782–792.

Ahmad

Bin Hidthiir

M. H.

Rahman

M. M.

Junoh

M. Z. M.

Yusof

M. F. B.

(2025). Impact of TBL-based CSR disclosure on financial performance in halal food companies: A system GMM analysis. SAGE Open, 15(1), 1–16.

Ahmad

Hidthiir

M. H. B.

Rahman

M. M.

(2024). Impact of CSR disclosure on profitability and firm performance of Malaysian halal food companies. Discover Sustainability, 5(1), 18.

Ali

M. A.

Hussin

H. A. A. A.

Amin

Y. S. A.

Tayfor

A. E.

Ahmad

(2025). Impact of AI Transformation, Financial Inclusion, and Operational Efficiency on Global Economic Growth: Dynamic GMM Approach. Qubahan Academic Journal, 5(4), 595–612.

Al-Shaer

Aldboush

H. H.

Alnajjar

A. H.

(2024). Corporate governance and firm performance: In Qatari non-financial firms. Journal of Islamic Accounting and Business Research. Advance online publication.

Altuntas

Berry-Stölzle

T. R.

Cummins

J. D.

(2021). Enterprise risk management and economies of scale and scope: Evidence from the German insurance industry. Annals of Operations Research, 299(1), 811–845.

Amel-Zadeh

Serafeim

(2018). Why and how investors use ESG information: Evidence from a global survey. Financial Analysts Journal, 74(3), 87–103. https://doi.org/10.2469/faj.v74.n3.2

Arellano

Bond

(1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The Review of Economic Studies, 58(2), 277–297. https://doi.org/10.2307/2297968

Bank of Thailand. (2024). Thailand green taxonomy: Phase II. BOT.

10.

bin Hidthiir

M. H.

Ahmad

Lun

L. K.

Mansur

Abubakr

A. A. M.

Sahal

M. S. G.

(2024). Determinants of government debt in ASEAN-5 nations: An ARDL analysis of economic factors. Qubahan Academic Journal, 4(4), 250–267.

11.

Bin Hidthir

M. H.

Khan

A. A.

Junoh

M. Z. M.

Yusof

M. F. B.

Ahmad

(2025). Development of the financial composite index for MENA region: A two-staged principal components analysis. SAGE Open, 15(1), 1–17.

12.

Bloomberg

L. P.

(2023). Bloomberg terminal: ESG data and analytics. https://www.bloomberg.com/professional/solution/sustainable-finance/

13.

Blundell

Bond

(1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115–143. https://doi.org/10.1016/S0304-4076(98)00009-8

14.

Cesarone

Martino

M. L.

Carleo

(2022). Does ESG impact really enhance portfolio profitability? Sustainability, 14(4), 2050.

15.

Chen

Song

Gao

(2023). Environmental, social, and governance (ESG) performance and financial outcomes: Analyzing the impact of ESG on financial performance. Journal of Environmental Management, 345, 118829.

16.

Coad

Segarra

Teruel

(2018). Innovation and firm growth: Does firm age play a role? Research Policy, 47(4), 775–786. https://doi.org/10.1016/j.respol.2018.02.012

17.

Collective Action Coalition Against Corruption (CAC). (2023). Annual report on certified companies. CAC Secretariat.

18.

Dang

Yang

(2018). Measuring firm size in empirical corporate finance. Journal of Banking & Finance, 86, 159–176. https://doi.org/10.1016/j.jbankfin.2017.09.006

19.

DeGeorge

Patel

Zeckhauser

(2013). Earnings management to exceed thresholds. The Journal of Business, 72(1), 1–33.

20.

Delmas

M. A.

Nairn-Birch

Lim

(2015). Dynamics of environmental and financial performance: The case of greenhouse gas emissions. Organization & Environment, 28(4), 374–393. https://doi.org/10.1177/1086026615575175

21.

Demsetz

Villalonga

(2001). Ownership structure and corporate performance. Journal of Corporate Finance, 7(3), 209–233. https://doi.org/10.1016/S0929-1199(01)00020-7

22.

Dittmar

Mahrt-Smith

(2007). Corporate governance and the value of cash holdings. Journal of Financial Economics, 83(3), 599–634. https://doi.org/10.1016/j.jfineco.2005.12.006

23.

Drempetic

Klein

Zwergel

(2020). The influence of firm size on the ESG score: Corporate sustainability ratings under review. Journal of Business Ethics, 167(2), 333–360.

24.

Eccles

R. G.

Ioannou

Serafeim

(2014). The impact of corporate sustainability on organizational processes and performance. Management Science, 60(11), 2835–2857. https://doi.org/10.1287/mnsc.2014.1984

25.

Eugene

F. F.

French

K. R.

(1992). The cross-section of expected stock returns. The Journal of Finance, 47(2), 427–465. https://doi.org/10.1111/j.1540-6261.1992.tb04398.x

26.

Eric

Maksim

Qian

(2022). How news reports and ESG publication financially affect firms. Корпоративные финансы, 16(3), 38–62.

27.

Fahad

Busru

S. A.

(2021). CSR disclosure and firm performance: Evidence from an emerging market. Corporate Governance: The International Journal of Business in Society, 21(4), 553–568.

28.

Fatemi

Glaum

Kaiser

(2018). ESG performance and firm value: The moderating role of disclosure. Global Finance Journal, 38, 45–64. https://doi.org/10.1016/j.gfj.2017.03.001

29.

Ferreira

M. A.

Vilela

A. S.

(2004). Why do firms hold cash? Evidence from EMU countries. European Financial Management, 10(2), 295–319. https://doi.org/10.1111/j.1354-7798.2004.00251.x

30.

Freeman

R. E.

(1984). Strategic management: A stakeholder approach. Pitman.

31.

Friede

Busch

Bassen

(2015). ESG and financial performance: Aggregated evidence from more than 2000 empirical studies. Journal of Sustainable Finance & Investment, 5(4), 210–233. https://doi.org/10.1080/20430795.2015.1118917

32.

Hejazi

Gholami

Sarraf

(2016). Relationship between Tobin’s Q and financial performance: Evidence from Iran. Journal of Finance and Accounting, 4(3), 56–61. https://doi.org/10.11648/j.jfa.20160403.12

33.

Hidthiir

M. H. B.

Ahmad

Anuar

A. R.

(2025). Impact of Covid-19 on Asean-5 economy: Strategy and policy. Greenbook Publisher.

34.

Hidthiir

M. H. B.

Ahmad

Junoh

M. Z. M.

Yusof

M. F. B.

(2024). Dynamics of economic growth in ASEAN-5 countries: A panel ARDL approach. Discover Sustainability, 5(1), 145.

35.

Huang

Bai

Shang

Ahmad

(2023). On the fast track: The benefits of ESG performance on the commercial credit financing. Environmental Science and Pollution Research, 30(35), 83961–83974.

36.

International Financial Reporting Standards (IFRS). (2023). IFRS S1 and S2: Sustainability disclosure standards. IFRS Foundation.

37.

Isa

M. Y.

Bahaman

M. A.

Ahmad

Islamkulov

Ahmed

(2025). Impact of global boycotts on Israeli goods: Evidence from Islamic and non-Islamic countries using an event study approach. Asian Economic and Financial Review, 15(7), 1111–1124.

38.

Jensen

M. C.

(1986). Agency costs of free cash flow, corporate finance, and takeovers. The American Economic Review, 76(2), 323–329.

39.

Jensen

M. C.

Meckling

W. H.

(1976). Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of Financial Economics, 3(4), 305–360. https://doi.org/10.1016/0304-405X(76)90026-X

40.

Jinga

(2021). The increasing importance of environmental, social and governance (ESG) investing in combating climate change. Environmental Management-Pollution, Habitat, Ecology, and Sustainability, 2, 279

41.

Junius

Adisurjo

Rijanto

Y. A.

Adelina

Y. E.

(2020). The impact of ESG performance to firm performance and market value. Jurnal Aplikasi Akuntansi, 5(1), 21–41.

42.

Khan

A. A.

Hidthiir

M. H. B.

Ahmad

Mansur

(2025a). Impact of human capital and governance in enhancing financial reachability in selected developing countries. Discover Sustainability, 6(1), 1–11.

43.

Khan

A. A.

Hidthir

M. H. B.

Mansur

Ahmad

(2025b). Role of financial inclusion in enhancing the effect of remittance on economic growth in developing countries. Cogent Economics & Finance, 13(1), 2476093.

44.

Knoll

Schularick

Steger

(2017). No price like home: Global house prices, 1870–2012. American Economic Review, 107(2), 331–353.

45.

(2016). Application of generalized method of moments (GMM) in panel data analysis: A comprehensive review. Journal of Economics and Management, 24(3), 45–60.

46.

Majumdar

S. K.

(1997). The impact of size and age on firm-level performance: Some evidence from India. Review of Industrial Organization, 12(2), 231–241. https://doi.org/10.1023/A:1007766324749

47.

Ministry of Finance. (2023). Thailand sustainable finance roadmap. Government of Thailand.

48.

Myers

S. C.

(1977). Determinants of corporate borrowing. Journal of Financial Economics, 5(2), 147–175. https://doi.org/10.1016/0304-405X(77)90015-0

49.

Mysaka

Vasylchak

Shevchenko

(2021). The effect of Tobin’s Q on investment efficiency in transition economies. Economic Studies Journal, 30(5), 18–32.

50.

Nguyen

H. T.

Kim

Pyo

(2016). The impact of cash holdings on firm performance in the presence of political connections: Evidence from Vietnam. Emerging Markets Finance and Trade, 52(4), 1065–1081. https://doi.org/10.1080/1540496X.2015.1080506

51.

Rahman

M. M.

Ahmad

Mokal

M. N.

Aziz

M. F.

Khotib

N. A. M.

(2024). Green sustainability and financial performance of halal food companies: Evidence of Malaysia. Journal of Islamic Monetary Economics and Finance, 10(4), 709–734.

52.

Rajan

R. G.

Zingales

(1995). What do we know about capital structure? Some evidence from international data. The Journal of Finance, 50(5), 1421–1460. https://doi.org/10.1111/j.1540-6261.1995.tb05184.x

53.

Roodman

(2009). How to do xtabond2: An introduction to difference and system GMM in Stata. The Stata Journal, 9(1), 86–136. https://doi.org/10.1177/1536867X0900900106

54.

Saliah

S. M.

Nadarajan

Teong

L. K.

(2023). Procurement category management process: Alignment to industry 4.0. They Seybold Report, 18(2), 1628–1638. https://doi.org/10.17605/OSF.IO/SD7GQ

55.

Saliah

S. M.

Nadarajan

Teong

L. K.

(2024). The influencing factors of sustainable procurement category management process in the MSMEs in the state of Tamil Nadu, India: Using PRISMA and AHP. International Journal of Procurement Management, 21(3), 302–323.

56.

Sandberg

Alnoor

Tiberius

(2023). Environmental, social, and governance ratings and financial performance: Evidence from the European food industry. Business Strategy and the Environment, 32(4), 2471–2489.

57.

Shirui

Mansur

Hidthiir

M. H. B.

Ahmad

Abubakr

A. A. M.

(2025). The impact of digital financial inclusion on household financial vulnerability in China: An empirical study based on CFPS. Asian Economic and Financial Review, 15(12), 1834–1853. https://doi.org/10.55493/5002.v15i12.5681

58.

Singh

Whittington

(1975). The size and growth of firms. The Review of Economic Studies, 42(1), 15–26. https://doi.org/10.2307/2296405

59.

Spence

(1973). Job market signaling. The Quarterly Journal of Economics, 87(3), 355–374. https://doi.org/10.2307/1882010

60.

Stock Exchange of Thailand (SET). (2023a). ESG disclosure guidelines for listed companies. SET.

61.

Stock Exchange of Thailand (SET). (2023b). SET ESG index methodology. SET.

62.

Sunitha

Manjula

S. S. P. D. K.

Gurusamy

(2024). Analyzing the impact of ESG factors on financial performance: A study of Indian corporations. Library Progress International, 44(3), 8253–8266.

63.

Transparency International. (2022). Corruption perceptions in Thailand: Sectoral analysis. Transparency International.

64.

Verbeke

Tung

(2013). The future of stakeholder management theory: A temporal perspective. Journal of Business Ethics, 112, 529–543.

65.

Wang

Yuan

Suo

Huang

Lin

(2024). Strategic imperatives of ESG in fostering corporate digital innovation: A resource-based view. Journal of the Knowledge Economy. Advance online publication.

66.

Wattanatorn

Kleinhans

(2024). ESG ratings and firm value: Evidence from the Thai stock market. Asian Journal of Sustainability and Business, 13(2), 55–72.

67.

(2022). The impact of ESG performance on firm value: The moderating role of ownership structure. Sustainability, 14(21), 14507.

68.

Yang

Zhou

Liu

(2024). E, S, and G, not ESG: Heterogeneous effects of environmental, social, and governance disclosure on green innovation. Corporate Social Responsibility and Environmental Management, 31(2), 1220–1238.

69.

Zhou

Liu

Luo

(2022). Sustainable development, ESG performance and company market value: Mediating effect of financial performance. Business Strategy and the Environment, 31(7), 3371–3387.

70.

Zumente

Bistrova

(2021). ESG importance for long-term shareholder value creation: Literature vs. practice. Journal of Open Innovation: Technology, Market, and Complexity, 7(2), 127.

Impact of ESG Performance on Profitability and Firm Value: Experience of Companies Listed on the Stock Exchange of Thailand

Abstract

Plain Language Summary

Keywords

Introduction

Literature Review and Hypothesis Development

ESG Performance and Financial Profitability

ESG Performance and Firm Value

Methodology

Sample and Data Collection

Variables and Measures

Dependent Variables

Independent Variables

Control Variables

Model Specification and Analytical Techniques

Result and Discussion

Robustness Result

Policy Implications

Conclusion and Future Research

Footnotes

ORCID iDs

Ethical Considerations

Consent to Participate

Consent for Publication

Funding

Declaration of Conflicting Interests

Data Availability Statement

References