Abstract
Green-finance practices are central to sustainable development across emerging Asian economies; however, their effectiveness varies widely due to limited understanding of how regulatory, organizational, and technological factors coexist and shape outcomes. This study develops and empirically examines an integrated, multi-level framework that links regulatory pressure, organizational capabilities, and digital transformation with banks' Environmental, Social, and Governance (ESG) performance. Drawing on Institutional Theory, the Resource-Based View, and Stakeholder Theory, it applies a fixed-effects regression model to secondary panel data from 10 commercial banks in Bangladesh, China, India, Indonesia, and Pakistan over 2015–2024. The analysis identifies a strong positive association between regulatory pressure and ESG performance and a significant relationship between organizational capabilities and ESG outcomes. More importantly, digital transformation shows a substantial moderating association, intensifying the influence of internal capabilities while exhibiting no independent direct effect on ESG results. These findings suggest that while regulation acts as a catalyst promoting sustainable-banking adoption, sustained ESG progress depends on the complementary alignment of digital infrastructure and organizational resource development. The study concludes with policy and managerial recommendations to strengthen such integrative pathways.
1 Introduction
The global financial system is undergoing a profound structural transformation driven by climate change, environmental degradation, social inequality, and rising expectations for corporate accountability. Within this evolving landscape, the banking sector—traditionally perceived as a financial intermediary—has become a key agent in steering economic systems toward sustainability. This shift is reflected in the growing adoption of green finance principles and ESG standards that embed sustainability considerations into core banking operations ().
The transition toward sustainable banking is particularly significant in emerging Asian economies such as Bangladesh, China, India, Indonesia, and Pakistan, where rapid industrial growth, environmental stress, and expanding financial systems intersect. Over the past decade, regulators in these countries have introduced green banking guidelines, sustainable finance taxonomies, and mandatory ESG disclosure frameworks aimed at channeling financial resources toward environmentally and socially responsible sectors (). Parallel to these regulatory initiatives has been a marked rise in sustainable bonds, green credit products, and ESG-based investment instruments, contributing to the region's growing prominence in the global sustainable finance landscape (). Despite these advancements, the implementation of sustainable banking practices remains inconsistent across the region. One major challenge lies in the limited understanding of how various institutional, organizational, and technological drivers interact to shape ESG outcomes. Existing research often examines these factors in isolation, resulting in fragmented insights and inconclusive evidence on what truly determines effective ESG performance in banks (; ). While some studies report enhanced corporate reputation, reduced financing costs, and improved stakeholder trust, others document weak or even negative short-term financial effects, especially in markets where implementation costs are high and green finance demand remains immature. These inconsistencies suggest that sustainability outcomes are not automatic but depend on the dynamic interplay between regulatory pressure, internal capabilities, and enabling technologies within banks ().
At the same time, digital transformation is rapidly reshaping the foundations of financial intermediation across Asia. The expansion of mobile banking, fintech innovation, artificial intelligence, and big data analytics has revolutionized how financial institutions operate (). These technologies can enhance transparency, streamline sustainability reporting, and strengthen risk management systems, thereby making green finance more efficient and credible (). However, the degree to which digitalization supports or accelerates sustainable banking outcomes remains underexplored in empirical literature, particularly in emerging markets where both digital and sustainability transitions are still evolving (). Understanding these interconnected relationships is essential for both policymakers and bank executives. Emerging Asian economies are simultaneously grappling with the demands of sustainable growth and the urgency of digital modernization. Regulatory reforms alone may not guarantee meaningful sustainability outcomes unless they are supported by strong organizational capabilities and strategic digital transformation. Without such integration, sustainability initiatives risk remaining superficial—focused on compliance rather than measurable impact. Against this backdrop, the present study investigates how regulatory initiatives, internal organizational capacities, and digital transformation jointly influence the ESG performance of banks in emerging Asian economies. By developing and empirically testing a multi-level framework using panel data from 2015 to 2024, this study provides evidence-based insights to inform policies and management strategies that align digital innovation with sustainable finance goals across the region.
The following sections of the paper are organized as follows. Section 2 presents the literature review, summarizing prior research on sustainable banking, ESG performance, and the evolving role of digital transformation in emerging Asian economies, while also outlining the research gap and contribution, conceptual model, and hypotheses. Section 3 details the research methodology, including data sources, variable measurement, and the econometric model employed for hypothesis testing. Section 4 reports the results and data analysis, discussing the key empirical findings and their implications. Finally, Section 5 provides the discussion and conclusion, highlighting the main insights, policy and managerial implications, and directions for future research.
2 Literature review
2.1 Sustainable banking in emerging Asia: institutional and performance perspectives
Research on sustainable banking in emerging Asian economies has evolved substantially over the past decade, moving from an early focus on corporate social responsibility () toward viewing sustainability as a strategic imperative shaped by financial, regulatory, and institutional contexts. This shift reflects a growing recognition that climate and sustainability exposures translate into material financial risks, prompting banks to embed environmental and social considerations within their core decision-making processes, including credit allocation, risk management, and long-term value creation. Policymakers have reinforced this transition through initiatives such as green-banking guidelines, sustainable-finance taxonomies, and mandatory ESG-disclosure frameworks introduced by central banks across South and Southeast Asia (). Evidence from Bangladesh, Pakistan, and India indicates that stronger regulatory enforcement tends to expand green lending, enhance environmental screening, and promote deeper integration of sustainability practices (; ; ).
However, the impact of these regulatory measures has been uneven. Differences in institutional maturity, political stability, and market development continue to shape outcomes, revealing that policy mandates alone cannot ensure uniform ESG improvements. The effectiveness of sustainable-banking reforms also depends on each institution's internal organizational capabilities, including managerial commitment, employee expertise, and a culture supportive of sustainability integration (; ). Banks with robust ESG governance structures and targeted staff-training programs typically outperform those engaging in symbolic compliance, whereas internal barriers such as limited technical capacity or resistance to change restrict policy translation into practice (; ; ).
Parallel to these institutional and organizational dynamics, scholars continue to debate the performance implications of adopting sustainable-banking practices. While several studies report that ESG orientation enhances profitability through improved risk management, lower funding costs, and stronger stakeholder trust (), others find neutral or negative short-term effects, particularly in emerging markets where compliance costs are high and demand for green financial products remains limited. These mixed results suggest that the financial benefits of sustainability are neither automatic nor universal but instead contingent upon contextual conditions, regulatory design, and the capacity of banks to operationalize sustainability strategies effectively. Hence, sustainable banking in emerging Asia is shaped by a complex interplay between external regulatory pressures and internal organizational readiness. Strong institutional frameworks provide direction, but tangible ESG improvements depend on banks' managerial, technical, and cultural capabilities to implement such reforms successfully.
2.2 Organizational capabilities, implementation constraints, and the integrative role of digital transformation
A growing consensus in the literature holds that the effectiveness of sustainable banking depends on the interaction between regulatory frameworks, organizational capacity, and an enabling technological environment. Earlier studies on emerging Asian economies underscore that formal compliance mechanisms alone are insufficient to secure sustainable outcomes unless supported by banks' internal resources and managerial capabilities (; ). While institutional structures initiate the sustainability agenda, the depth of implementation depends on whether banks possess sufficient technical expertise, human capital, and governance systems to translate regulatory directives into measurable ESG progress. However, internal barriers such as limited staff training, weak sustainability awareness, and inertia in organizational change continue to constrain green-finance adoption (; ; ). Thus, the persistence of performance gaps across banks and countries reveals that capability development—not regulation alone—drives effective sustainability integration.
In more recent work, digital transformation (DT) has emerged as a decisive factor that connects institutional and organizational dynamics. Digitalization—through innovations such as mobile banking, fintech applications, artificial intelligence, and data analytics—has revolutionized financial intermediation, improving transparency, operational efficiency, and stakeholder communication (; ). Nevertheless, the literature remains divided on whether DT serves as an independent driver or merely a facilitator of ESG improvements. A critical synthesis of recent evidence (; ) shows that digital technology alone does not guarantee sustainable-banking outcomes; rather, it amplifies existing institutional pressures and internal capabilities when these are already in place. This finding challenges deterministic narratives that portray technology as inherently transformative, emphasizing instead that its impact is conditional on organizational readiness and regulatory alignment.
The coexistence of enabling and constraining factors is central to explaining the mixed empirical results reported across contexts. For instance, () observe that similar policy intent is undermined when organizations lack strategic capabilities or technological infrastructure. This comparative evidence suggests that regulation is a necessary but insufficient condition—effective ESG performance materializes only when regulatory coercion interacts with robust organizational competence and the supportive use of digital tools. In weak institutional environments, short-term compliance costs often outweigh benefits, while under stronger regulatory and capability conditions, those same costs evolve into long-term reputational and performance gains ().
This contextual pattern highlights a more complex theoretical relationship: digital transformation functions less as a driver and more as a mediator that links institutional coherence with organizational effectiveness. By digitizing information systems and risk-management processes, banks can strengthen compliance efficiency and reporting quality while enhancing transparency toward regulators and stakeholders (; ). Yet, as repeatedly noted, these outcomes depend on complementary interactions—technological modernization yields little sustainability progress when pursued independently of human expertise, resource mobilization, and policy consistency (; ). Hence, the literature emphasizes an interactionist view in which regulatory pressure triggers sustainable-banking adoption, organizational capabilities enable effective implementation, and digital transformation amplifies their combined impact. Together, these elements function as complementary and mutually reinforcing determinants of ESG performance in emerging Asian banking systems.
2.3 Research gap and contribution
Despite a steadily expanding body of literature, research on sustainable banking in emerging Asian economies remains fragmented and theoretically disjointed (). Most prior studies examine individual determinants in isolation—either focusing on regulatory influence (; ) or ORG ()—while neglecting how these forces interact to shape ESG outcomes. Very few studies explicitly consider the role of DT, and those that do tend to treat it as a background factor rather than as an active moderator that conditions the strength or direction of sustainability relationships (; ). Consequently, the synergistic interplay among institutional pressures, organizational resources, and technological advancement remains largely unexplored, leaving unclear how these multi-level mechanisms jointly influence banks' ESG performance in emerging Asia.
The present study directly addresses these theoretical and empirical gaps by developing an integrated multi-level framework that combines the foundations of Institutional Theory, the Resource-Based View (RBV), and Stakeholder Theory into a single, testable model of sustainable banking. Institutional Theory explains how regulatory coercion and legitimacy pressures initiate sustainable practices; RBV clarifies how internal resources and capabilities transform compliance into genuine performance outcomes; and Stakeholder Theory situates ESG adoption within broader expectations of accountability and legitimacy. Within this integrated structure, DT is innovatively conceptualized as an enabling moderator that amplifies the effect of ORG on ESG performance—enhancing transparency, efficiency, and responsiveness without acting as an independent driver. This theoretical precision reconciles earlier inconsistencies and aligns with recent evidence from artificial-intelligence and sustainability studies that view digital tools as catalysts requiring capable organizational environments to produce measurable sustainability gains ().
Methodologically, the research advances the field by introducing a multi-country, decade-long panel dataset covering five emerging Asian economies—Bangladesh, China, India, Indonesia, and Pakistan—from 2015 to 2024. Unlike prior country-specific studies (; ), this design enables simultaneous assessment of cross-country variation in regulatory frameworks and within-bank evolution over time. Applying a Fixed-Effects panel regression with robust standard errors, the study isolates bank-specific inertial effects and estimates both direct and moderating relationships that were previously unobservable across fragmented samples. Collectively, these contributions—conceptual integration across three major theories, empirical identification of DT as the missing moderating link, and methodological innovation through cross-national longitudinal analysis—represent a substantive step forward in sustainable-banking scholarship. The study thus moves beyond single-driver explanations to offer a comprehensive, evidence-based understanding of how REG, ORG, and DT converge to enhance ESG performance in the banking sectors of emerging Asian economies.
2.4 Conceptual framework, theoretical foundations, and hypothesis development
Building upon the preceding literature, this study develops an integrated multi-level framework that explains the ESG performance of banks in emerging Asian economies by examining how institutional pressures, ORG, and DT interact. The framework integrates three established theoretical perspectives—Institutional Theory, the Resource-Based View (RBV), and Stakeholder Theory—to clarify how external regulatory environments, internal resources, and technology together influence the success of sustainable banking (; ; ). Within this framework, DT operates as a moderating condition that strengthens how effectively internal resources convert external pressures into ESG outcomes. This relationship is particularly relevant in emerging Asian economies, where regulatory maturity and technological infrastructure differ widely (; ; ).
Institutional Theory provides the foundation for understanding REG as the external driver of sustainability adoption. Organizations often respond to coercive, normative, and mimetic pressures not only for efficiency but also to gain legitimacy (; ). In the banking sector, central bank directives, sustainability taxonomies, and mandatory ESG-disclosure rules create powerful institutional incentives that encourage banks to adopt green practices (). As noted in earlier studies, when regulations are well-defined and consistently enforced, banks tend to expand green lending, improve environmental screening, and strengthen ESG commitments. These observations support the expectation that stronger regulatory frameworks will lead to better ESG performance by formalizing sustainability requirements and reinforcing legitimacy-seeking behavior.
H1a (Institutional Effect): REG has a positive relationship with the adoption of sustainable-banking practices and ESG performance.
While regulation defines the external boundaries, the ability of banks to implement sustainable policies depends on their internal strengths. The RBV emphasizes that valuable and inimitable internal capabilities—such as managerial commitment, skilled staff, and effective ESG governance—allow organizations to transform compliance into measurable and sustained performance. Empirical studies in developing-country banking contexts confirm that such capacities differentiate institutions that achieve tangible sustainability outcomes from those that comply symbolically (; ; ). Within the integrated framework, ORG function as the enabling mechanism that converts institutional requirements into practice. When banks possess stronger ORG, REG is more likely to result in consistent ESG integration.
H1b (Organizational Effect): ORG positively influence sustainable-banking practices and ESG performance.
Stakeholder Theory complements these perspectives by emphasizing that organizations pursue sustainability to earn legitimacy and meet the expectations of regulators, investors, and communities (). ESG performance thus represents the tangible outcome of how external and internal mechanisms operate together. Banks that institutionalize sustainability not only comply with regulatory rules but also strengthen their credibility and stakeholder trust (; ). This outcome forms the basis for the expectation that improvements in sustainable-banking practices will translate into measurable progress in ESG indicators.
H1c (Performance Effect): The adoption of sustainable-banking practices is positively associated with improved ESG performance.
Beyond the institutional and organizational layers, recent scholarship underscores the central role of DT in shaping how effectively banks achieve their sustainability targets (; ; ). Digitalization introduces new tools such as big data analytics, artificial intelligence, and fintech platforms that enhance data accuracy, reporting efficiency, and stakeholder transparency. Prior studies emphasize that these technologies act as catalysts, improving how existing capabilities function rather than independently driving sustainability outcomes (). In this study, DT is conceptualized as a moderating mechanism that reinforces the relationship between ORG and ESG performance.
Three mechanisms observed in the literature explain this moderating role. First, improved data-processing capacity allows banks with strong sustainability management teams to integrate ESG information more effectively into lending and reporting decisions (). Second, the digitalization of compliance processes—such as environmental-risk monitoring and ESG disclosure—enables organizational systems to operate more efficiently and with fewer operational bottlenecks (). Third, the use of digital platforms improves transparency and stakeholder communication, allowing capable organizations to demonstrate sustainability progress in real time (; ). These mechanisms suggest that the positive impact of ORG on ESG outcomes strengthens as the level of digital integration increases, since technology enhances the efficiency and credibility of internal processes.
H2 (DT Effect): DT positively moderates the relationship between ORG and ESG performance, such that the effect of ORG on ESG outcomes is stronger at higher levels of DT.
Taken together, these relationships form the basis of an integrated multi-level model of sustainable banking. REG provides the initial institutional impetus, ORG determine implementation quality, and DT amplifies the results by improving efficiency, consistency, and visibility (; ). This combination also clarifies why sustainability outcomes differ across banks and countries even when regulatory frameworks appear similar (; ). Institutions embedded in digitally advanced and organizationally competent settings are better able to translate regulation into effective ESG performance.
H3 (Integrated Framework): The combined model significantly explains cross-country differences in ESG performance among banks in emerging Asian economies.
In sum, this conceptual framework positions REG as the initiating force, ORG as the enabling foundation, and DT as the amplifying mechanism of ESG performance in sustainable banking. The integration of Institutional Theory, RBV, and Stakeholder Theory provides a coherent and empirically testable rationale for examining how institutional context, internal readiness, and technological advancement interact to shape sustainability outcomes across the emerging Asian banking sector.
3 Research methodology
3.1 Focus of study and sample collection
The empirical setting focuses on commercial banks operating in five major emerging Asian economies—China, India, Indonesia, Bangladesh, and Pakistan. These countries were selected because they represent rapidly expanding financial systems, growing regulatory attention to sustainable and green banking, and diverse institutional environments that allow meaningful cross-country comparison of ESG performance. The target population includes all licensed commercial banks in these economies; however, the final sample is restricted to those that meet three inclusion criteria: (1) consistent availability of ESG performance information; (2) availability of financial and organizational data required to construct the explanatory variables; and (3) continuous operation throughout the study period. Banks are excluded if they fail to disclose ESG measures for multiple years, are newly established within the sample window, or report incomplete financial statements, as these issues would weaken panel consistency and compromise estimation reliability. Applying these criteria results in a balanced panel of 10 commercial banks observed annually from 2015 to 2024, yielding 100 bank-year observations.
Although, a sample of 10 banks (N = 100 bank-year observations) is relatively modest, it remains appropriate and sufficient for the analytical objectives of this research for several reasons. First, the Fixed-Effects (FE) panel estimator controls for all time-invariant, bank-specific heterogeneity, meaning that the within-bank variation over 10 years is the main identification source, providing considerable statistical power even with a relatively small cross-sectional unit. Second, the study emphasizes comparability and data completeness rather than sample breadth: only banks with consistent ESG reporting over the full 2015–2024 period were retained, as including partially reported observations could introduce measurement error and bias the estimates, especially for the interaction term. Third, the cross-country design, encompassing five distinct regulatory settings—Bangladesh, China, India, Indonesia, and Pakistan—ensures meaningful institutional heterogeneity not attainable in a single-country, larger-sample design. Finally, similar sample sizes have been employed in comparable ESG-banking panel studies in emerging Asia, reflecting the region's data-availability limitations. Future research should extend this framework to broader samples as ESG disclosure databases for emerging-market banks expand.
Data are compiled from multiple secondary sources to ensure robust construct coverage. ESG performance data are obtained from standardized rating providers such as Refinitiv Eikon and Bloomberg, which report composite scores based on environmental, social, and governance dimensions. Organizational and financial information—including balance-sheet and income-statement indicators used to proxy internal capacity and controls—is collected from annual reports and databases such as Compustat Global and BankScope. REG is constructed through a systematic review of central-bank regulations, green-banking guidelines, and sustainable-finance directives applicable in each country during the study period, allowing the study to distinguish between stronger mandatory regimes and more voluntary frameworks.
3.2 Variables and data sources
As presented in Table 1, all variables in this study are defined and measured in accordance with its three theoretical foundations—Institutional Theory, the Resource-Based View (RBV), and Stakeholder Theory. DT serves as a connecting mechanism that links institutional and organizational factors to sustainability outcomes. This design ensures that each construct is both theoretically justified and empirically measurable across banks and countries in the sample.
Table 1
| Variable | Definition in context | Measurement/calculation | Role in model |
|---|---|---|---|
| ESG performance (ESG) | Composite measure of environmental, social, and governance outcomes | Refinitiv/Bloomberg composite ESG score (0–100 scale). | Dependent variable |
| Regulatory Pressure (REG) | Degree of mandatory green banking regulations and enforcement | Log of Total Assets [Ln(TA)] as a proxy for size/capacity, and the ratio of Non-Interest Expense to Total Assets (to proxy operating efficiency/investment in internal systems). | Independent variable |
| Organizational capabilities (ORG) | Internal expertise, managerial commitment, and sustainability structures | Variable: 1 if the country has mandatory, prescriptive green banking regulations; 0 otherwise. | Independent variable |
| Digital transformation (DT) | Integration of advanced digital technologies in banking operations | IT Investment Intensity: Measured as the ratio of Information Technology (IT) expenses to total operating expenses. | Moderating variable |
Econometric variable operationalization and measurement.
The dependent variable, ESG performance, captures the core sustainability outcome of the analytical framework. It is measured using a composite ESG score from reputable data providers such as Refinitiv Eikon and Bloomberg, which consolidate environmental, social, and governance indicators into a standardized 0–100 index. Following Stakeholder Theory, this variable reflects the extent to which banks meet the expectations of investors, regulators, customers, and society at large. Higher ESG scores indicate stronger fulfillment of stakeholder responsibilities and demonstrate the degree to which banks translate regulatory compliance and internal capacity into credible sustainability performance. Building on this outcome perspective, the first independent variable, REG, represents the institutional conditions influencing ESG performance. In line with Institutional Theory, REG captures the external coercive and normative pressures created by central banks, governments, and supervisory agencies through sustainable-banking policies and green-finance regulations. These forces shape banks' legitimacy-seeking behavior and drive ESG adoption. REG is operationalized in two complementary ways: (1) as a binary measure distinguishing between mandatory (1) and voluntary (0) regulatory frameworks, and (2) as a regulatory-strength index systematically derived from official policy documents. This dual approach captures variation in both the existence and intensity of institutional oversight, defining the external boundaries within which banks sustain formalized sustainability practices.
Within these institutional boundaries, internal capacity determines the extent and quality of implementation. The second independent variable, ORG, arises directly from the RBV and represents each bank's ability to mobilize tangible and intangible resources in support of sustainability objectives. ORG is proxied using two bank-level metrics: the log of total assets, which captures available scale and resource depth, and the ratio of non-interest expenses to total assets, which reflects investments in systems, staff, and internal processes. Higher ORG values imply stronger institutional readiness and managerial capacity to translate regulatory expectations into practical ESG outcomes, aligning with RBV assumptions that firms with superior resources perform better in adaptive and sustainability contexts.
Complementing these external and internal dimensions, the moderating variable, DT, acts as an integrative mechanism that enhances synergy between regulatory influence and organizational strength. DT is measured by IT investment intensity, calculated as the ratio of IT-related expenses to total operating expenses, reflecting the degree to which digital tools and systems are embedded within a bank's operations. Although not confined to one theoretical base, DT bridges all three perspectives: under Institutional Theory, it facilitates compliance monitoring and ESG reporting; under RBV, it boosts resource utilization and innovation; and under Stakeholder Theory, it enhances transparency and communication with stakeholders. Accordingly, DT is expected to strengthen the positive effect of ORG on ESG performance rather than exert a direct independent influence. Finally, to account for alternative explanations, the model incorporates control variables widely used in sustainable-finance research. These include profitability (measured by return on assets, ROA), bank size (derived from total assets), and other relevant bank-level or macroeconomic controls depending on data availability. Including these controls ensures that the estimated relationships reflect genuine institutional, organizational, and technological influences on ESG outcomes rather than underlying financial-performance effects.
3.3 Empirical modeling
The study applies a series of econometric approaches to test the hypotheses. First, it reports descriptive statistics and examines variation across banks and over time in ESG performance, REG, ORG, DT, and the control variables. This step provides the empirical context needed to interpret subsequent findings and demonstrates substantial dispersion in the variables, supporting the use of panel-based techniques that can handle cross-sectional and time-series heterogeneity. Trend figures are also used to summarize how key variables change during the 2015–2024 period. Second, the study assesses preliminary associations among variables using Pearson correlation analysis. The correlation matrix offers an initial indication of whether ESG performance is positively associated with REG, ORG, and DT, and it also helps identify whether the explanatory variables are overly correlated with each other. Following conventional thresholds, correlations well-below 0.80 are taken as evidence that severe multicollinearity is unlikely, which justifies including the predictors together in the panel regression models.
Third, the study estimates the main associations using a Fixed-Effects (FE) panel regression framework. The FE approach controls for unobserved, time-invariant, bank-specific characteristics—such as persistent governance practices, organizational culture, or business-model differences—that may confound observed relationships. The estimation proceeds through model comparison consistent with the Results tables: a baseline model estimates the associations between ESG performance and the direct predictors (REG and ORG) while including controls such as bank size and profitability. A second model extends the baseline specification by adding DT and an interaction between ORG and DT to examine whether the association between organizational capabilities and ESG performance becomes stronger at higher levels of digital transformation. The moderation hypothesis is treated as supported when the interaction term is positive and statistically significant, indicating that DT is associated with a strengthening of the ORG–ESG relationship.
To strengthen the reliability of statistical inference, the estimation uses robust standard errors to address heteroskedasticity and potential serial correlation common in financial panel data. Multicollinearity diagnostics (such as VIF checks) are also applied, and interaction-related overlap is reduced by constructing the interaction term using mean-centered variables. Overall, this approach produces results that can be interpreted as robust empirical associations consistent with the structure of the descriptive statistics, correlation patterns, and fixed-effects regression outputs reported in the Results section.
4 Results and data analysis
This section reports the empirical findings of the study using secondary panel data from 10 commercial banks (two from each country) operating in China, India, Indonesia, Bangladesh, and Pakistan over 2015–2024, yielding a balanced dataset of 100 bank-year observations. The analysis follows a clear sequence: it first describes the sample and key variable patterns, then examines bivariate associations through correlations, and finally tests the study's hypotheses using a Fixed-Effects (FE) panel regression framework. This structure provides descriptive context, assesses the suitability of the empirical model, and presents the final evidence used to evaluate the integrated framework.
4.1 Descriptive statistics and sample characteristics
Table 2 summarizes the descriptive statistics for the full panel. The results show meaningful variation across banks and time in both the dependent and explanatory variables. ESG performance has a mean of 60.603 with a relatively large standard deviation (15.458), indicating substantial dispersion in sustainability outcomes across the sample. REG also varies considerably (mean 0.648, standard deviation 0.478), suggesting that banks operate under different regulatory conditions across countries and years. ORG and DT display notable variability as well (ORG mean 0.148, standard deviation 0.040; DT mean 0.064, standard deviation 0.020), supporting the view that internal capacity and digital maturity differ across banks. The control variables likewise display dispersion, particularly bank size (SIZE) and profitability (ROA). Overall, the observed cross-sectional and temporal heterogeneity supports the use of panel-based estimation, which allows the analysis to leverage within-bank changes over time while also accounting for differences across banks. Trend visualization (Figure 1) complements Table 2 and Figure 2 by illustrating how the key variables evolve between 2015 and 2024. Presenting these trajectories helps motivate the panel approach by showing that the main constructs are not static and that time variation is an important feature of the data.
Table 2
| Variable | Symbol | Observations | Mean | Standard deviation | Min. | Max. |
|---|---|---|---|---|---|---|
| ESG performance | ESG | 100 | 60.603 | 15.458 | 21.0 | 97.0 |
| Regulatory pressure | REG | 100 | 0.648 | 0.478 | 0.00 | 1.000 |
| Organizational capabilities | ORG | 100 | 0.148 | 0.040 | 0.030 | 0.274 |
| Digital transformation | DT | 100 | 0.064 | 0.020 | 0.010 | 0.108 |
| Control: bank size | SIZE | 100 | 18.976 | 1.522 | 16.00 | 23.800 |
| Control: profitability | ROA | 100 | 2.560 | 1.251 | −1.500 | 5.8 |
Summary statistics of panel data variables.
Figure 1
Figure 2
Table 2 reveals that ESG performance shows an average level across the sample, with high dispersion among banks, indicating substantial cross-sectional and time-series variation. REG, ORG, and DT also exhibit significant variability, justifying the use of a Fixed-Effects (FE) panel model for empirical estimation. The observed variation between banks and over time confirms the suitability of the panel-regression methodology for testing the study's hypotheses.
4.2 Correlation analysis (bivariate associations)
Table 3 reports Pearson correlation coefficients to assess initial associations between ESG performance and the main predictors, as well as to test whether the explanatory variables are excessively correlated with one another. The results show that ESG performance is positively and statistically significantly associated with REG (r = 0.35, p < 0.01), ORG (r = 0.42, p < 0.01), and DT (r = 0.38, p < 0.01). These bivariate patterns align with the conceptual expectation that stronger regulatory environments, greater organizational capacity, and higher digital-investment intensity are each linked to better ESG scores. Importantly, correlations among the independent variables remain well-below common multicollinearity thresholds. The highest reported correlation among the predictors is between ORG and DT (r = 0.31, p < 0.01), which is moderate and does not indicate serious overlap. Taken together, the correlation matrix supports the inclusion of REG, ORG, and DT in the same regression specification and provides preliminary evidence that the proposed relationships are plausible at the association level.
Table 3
| Variables | ESG | REG | ORG | DT | ROA | SIZE |
|---|---|---|---|---|---|---|
| ESG | 1.000 | |||||
| REG | 0.35** | 1.000 | ||||
| ORG | 0.42** | 0.21** | 1.000 | |||
| DT | 0.38** | 0.15* | 0.31** | 1.000 | ||
| ROA | 0.10 | 0.05 | 0.18** | 0.08 | 1.000 | |
| SIZE | 0.25** | 0.12* | 0.29** | 0.19** | 0.15* | 1.000 |
Correlation matrix of model variables.
*p < 0.05; **p < 0.01.
These findings mean that, there are moderate relationships between the explanatory variables with no sign of serious multicollinearity. The correlation pattern justifies the appropriateness of the variables to be included in the panel regression forms that will be outlined in the empirical modeling section.
4.3 Panel regression results (model comparison and hypothesis testing)
Table 4 presents the main hypothesis-testing results using a Fixed-Effects (FE) panel-regression framework. The estimates are reported in two specifications to clearly distinguish direct associations from moderation effects. Model 1 reports the direct associations of REG and ORG with ESG performance (along with control variables). Model 2 extends Model 1 by incorporating DT and the interaction term between ORG and DT to evaluate the moderation hypothesis. Across both models, REG shows a positive and statistically significant coefficient at the 1% level (approximately 4.49–4.51), indicating that stronger regulatory settings are associated with higher ESG performance within the FE framework. ORG also remains positive and statistically significant at the 1% level (approximately 18.20–18.21), suggesting that greater internal capability is consistently linked to higher ESG scores.
Table 4
| Independent variable | Model 1 (direct effects) | Model 2 (moderation test) | Hypothesis tested |
|---|---|---|---|
| Regulatory pressure (REG) | 4.49*** | 4.51*** | H1a |
| (1.30) | (1.32) | Supported | |
| Organizational capabilities (ORG) | 18.20*** | 18.21*** | H1b |
| (4.11) | (4.09) | Supported | |
| Digital transformation (DT) | −5.97 | 13.71*** | Direct effect |
| (4.70) | (4.35) | Supported | |
| Interaction term (ORG × DT) | 35.80*** | H2 | |
| (7.10) | Supported | ||
| SIZE (control) | 1.35*** | 1.35*** | |
| (0.32) | (0.31) | ||
| ROA (control) | 0.10 | 0.10 | |
| (0.13) | (0.12) | ||
| Observations | 100 | 100 | |
| R2 (Within) | 0.984 | 0.984 |
Panel regression results: fixed effects moderation test.
***p < 0.01, **p < 0.05, and *p < 0.10.
The role of DT differs across model specifications. In Model 1, DT is not statistically significant; however, in Model 2, once the interaction term is introduced, DT becomes positive and statistically significant (13.71, p < 0.01). Most importantly, the interaction term (ORG × DT) in Model 2 is positive and statistically significant at the 1% level (35.80, p < 0.01). This finding supports the moderation hypothesis by demonstrating that the positive association between ORG and ESG performance strengthens at higher levels of DT. Regarding control variables, SIZE is positive and statistically significant, indicating that larger banks tend to achieve higher ESG scores. In contrast, profitability (ROA) is not statistically significant in either model, suggesting that short-term financial performance does not directly influence sustainability outcomes in this context.
5 Discussion and conclusion
5.1 Reasons for the results
The findings of this study reveal consistent associations between REG, ORG, DT, and ESG performance—relationships that reinforce established theoretical expectations while adding contextual depth. In line with Institutional Theory, stronger regulatory environments correspond with higher ESG performance, reflecting the influence of coercive pressures and the pursuit of legitimacy in shaping sustainability adoption (; ). This pattern supports evidence from South and Southeast Asia showing that formalized policy frameworks—such as green-finance guidelines and disclosure mandates—encourage compliance and strengthen accountability (; ; ). However, the results also indicate that regulations alone do not guarantee improved performance; their effectiveness depends on institutional quality and the organizational ability to translate policy goals into practice.
At the organizational level, the positive relationship between internal capabilities and ESG outcomes supports the Resource-Based View (RBV). Managerial commitment, governance infrastructure, and technical expertise remain decisive factors that turn compliance into substantive engagement (). In South Asian contexts, banks with strong ESG governance systems and trained sustainability staff achieve more consistent results than those where sustainability is largely symbolic. Organizational readiness therefore mediates how external pressures are interpreted, converted into internal processes, and sustained over time.
However, the finding that DT does not have a significant direct effect but strengthens the ORG–ESG relationship provides an important nuance to previous studies. In settings with advanced digital infrastructure, such as Chinese banks studied by (), technology has shown a direct positive impact on ESG performance. By contrast, the emerging-Asia sample here reflects uneven digital infrastructures, fragmented data systems, and limited staff expertise that constrain technology's standalone effectiveness. DT instead functions as a catalytic complement, improving reporting quality, risk screening, and information accuracy, but only when integrated into capable organizational systems (; ; ). The results indicate that the sustainability benefit of digitalization depends less on the scale of technological investment and more on how well-digital tools are aligned with managerial capacities and institutional maturity.
These patterns contribute to three main theoretical perspectives. First, the findings confirm Institutional Theory by showing that regulatory pressure produces meaningful change only under supportive institutional and technical conditions. Second, they extend RBV by demonstrating that internal capabilities both drive sustainability performance and determine how organizations absorb and apply external regulations and digital tools. Third, they link Stakeholder Theory with digitalization research by showing that technology primarily enhances transparency and accountability rather than directly determining ESG outcomes. Overall, DT emerges as a coordinating force that connects institutional mandates with organizational resources and enhances their combined influence on ESG performance. Rather than acting as an independent driver, it strengthens the relationship between regulatory alignment and internal readiness in producing sustainable banking outcomes (). This integrated understanding advances sustainable-finance research by showing that progress in emerging Asian banking depends on the joint development of regulation, capability, and technology within a supportive institutional setting.
5.2 Practical implications for stakeholders
The findings carry distinct implications for key stakeholder groups in emerging Asian banking systems. For regulators and central banks, the positive association between REG and ESG performance indicates that mandatory or strongly enforced frameworks can help steer banks toward more sustainability-oriented practices. At the same time, regulation alone is unlikely to ensure consistently high-quality ESG outcomes. Policymakers can enhance effectiveness by complementing regulatory pressure with capacity-building measures—such as investment in sector-level digital infrastructure, clearer and more standardized ESG disclosure guidance, and technical-training initiatives that strengthen banks' ability to implement sustainability requirements in practice.
For bank management, the results suggest that sustainable banking should be treated as a strategic and operational capability rather than a mere compliance exercise. Because ORG are positively associated with ESG performance—and this relationship becomes stronger at higher levels of DT—banks can benefit from aligning sustainability initiatives with targeted digital investments. In practice, this involves prioritizing tools that directly support sustainability execution, such as data analytics for environmental and social risk assessment, automated ESG reporting systems, and integrated dashboards that improve monitoring, accountability, and decision quality. Likewise, for investors and civil-society stakeholders, the findings suggest that variations in ESG performance across banks are partly shaped by structural factors beyond short-term financial outcomes, including regulatory context, organizational readiness, and digital maturity. Assessments of bank ESG performance are more informative when these contextual factors are considered—for example, the strength of green-banking regulation and the bank's level of digital capability—particularly when comparing institutions across different emerging-market settings.
5.3 Limitations and future research directions
This study has several limitations that open clear avenues for future research. First, the use of secondary panel data restricts the ability to make definitive causal claims. Although the Fixed-Effects approach helps control for time-invariant unobserved heterogeneity across banks, the results may still be influenced by reverse causality, omitted time-varying factors, and dynamic adjustment processes that are not explicitly captured. Second, DT is operationalized through IT-investment intensity, which is theoretically defensible but may not fully capture qualitative dimensions of digital maturity. Future studies could employ richer measures, including fintech-adoption indices, indicators of AI and analytics integration, the share of transactions conducted through digital channels, or externally validated digital-capability scores. Third, the study's sample-−10 banks across five emerging Asian economies—is relatively small and may not fully represent the diversity of the region's banking sector. While suitable for the analytical design, this limitation suggests that future work should expand sample coverage as ESG disclosure improves, enabling more robust generalization and finer cross-country comparison.
Fourth, the operationalization of regulatory pressure (REG) as a binary measure distinguishing mandatory vs. voluntary frameworks, while practical and consistent with prior literature, may oversimplify institutional heterogeneity. Future research could develop more nuanced indices that capture variations in enforcement quality, policy scope, and regulatory intensity to better reflect cross-country institutional differences. Finally, the study's regional scope narrows external validity. Focusing specifically on emerging Asian economies ensures comparability but constrains generalizability to other contexts. Future research could apply the framework to broader cross-regional samples and incorporate macro-institutional moderators such as governance quality, regulatory capacity, or financial-market development to explain cross-country differences more effectively. Additionally, further work could explore alternative model structures, including mediation pathways (for instance, whether DT channels part of the association between REG and ESG outcomes) and econometric techniques that strengthen causal inference. These extensions would refine methodological rigor and deepen understanding of how institutional, organizational, and technological dynamics jointly shape sustainable banking outcomes.
Statements
Data availability statement
The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.
Author contributions
MU: Writing – original draft, Writing – review & editing. MR: Writing – original draft, Writing – review & editing. JK: Writing – original draft, Writing – review & editing. JF: Writing – original draft, Writing – review & editing. SM: Writing – original draft, Writing – review & editing. JKP: Writing – original draft, Writing – review & editing. CL: Writing – original draft, Writing – review & editing. WM: Writing – original draft, Writing – review & editing.
Funding
The author(s) declared that financial support was received for this work and/or its publication. The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Hong Kong Government, Grant number (17606125); City University of Hong Kong, Grant number (7020093).
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Summary
Keywords
digital transformation, emerging Asian economies, ESG performance, financial institutions, green finance, sustainable banking
Citation
Ullah MF, Ridwan M, Ko J, Falzon J, Muhammad S, KP JM, Leung CK and Ming WK (2026) An integrated multi-level framework for sustainable banking and ESG performance: the critical role of digital transformation in emerging Asia. Front. Environ. Econ. 5:1822753. doi: 10.3389/frevc.2026.1822753
Received
04 March 2026
Revised
15 April 2026
Accepted
11 May 2026
Published
08 June 2026
Volume
5 - 2026
Edited by
Maria Markaki, Hellenic Mediterranean University, Greece
Reviewed by
Renju Chandran, Chinmaya Vishvavidyapeeth, India
Hanan Eid Badwy, University of Sadat City, Egypt
Updates
Copyright
© 2026 Ullah, Ridwan, Ko, Falzon, Muhammad, KP, Leung and Ming.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Mohammad Ridwan, m.ridwan.econ@gmail.com; Jeremy Ko, jereko@ethz.ch
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.