Digital transformation and sustainability performance: an empirical study from Indonesia

The rapid advancement of digital technology has transformed the global economy, shifting it from an industrial-based system to a digitally driven era (Yang et al., 2023). At the heart of this transformation lies corporate digitalization, which drives innovation, operational efficiency, and competitive advantage (Vial, 2019; Wu et al., 2023). Through technologies such as artificial intelligence (AI), big data, and blockchain, companies are reimagining business models, enhancing customer experiences, and integrating sustainability into their strategies (Lu et al., 2024; Zhang et al., 2024). However, the pace and scope of digital transformation vary widely depending on organizational capabilities and institutional environments (Sun et al., 2024; Verhoef et al., 2021).

At the same time, growing concerns about climate change, inequality, and resource depletion have heightened stakeholder expectations for sustainable corporate practices (Chen and Ren, 2025). Elkington’s (1998) triple bottom line framework underscores the need to balance economic, environmental, and social objectives. ESG scores have emerged as critical indicators of how effectively companies manage sustainability-related risks and align their business strategies with stakeholder demands (Chininga et al., 2023). Strong sustainability performance is increasingly associated with enhanced corporate reputation, investor confidence, and long-term competitiveness (Suhardjo et al., 2024a; Tan and Zhu, 2022).

The intersection of digital transformation and ESG extensively examined in developed economies, predominantly based on stakeholder theory, signal theory, information asymmetry theory, legitimacy theory, and neoclassical theory (Liu et al., 2024; Luo et al., 2024; Zhang et al., 2024). Studies in technologically advanced developing countries, such as China, report mixed results on this relationship (Luo et al., 2024; Wang and Hou, 2024). However, empirical evidence remains limited in countries with underdeveloped digital infrastructure.

This study aims to address this gap by examining the relationship between digital transformation and sustainability performance in Indonesian listed companies. Drawing on the resource-based view (RBV) and dynamic capability (DC) theories, we conceptualize digitalization as a strategic resource that enables firms to adapt and thrive in resource-constrained and institutionally diverse environments. This theoretical framing allows us to extend ESG-performance discourse beyond compliance-driven models toward capability-driven strategies that reflect the realities of emerging markets.

This study offers three distinct contributions to literature. First, it examines the relationship between digital transformation and sustainability performance in Indonesia, a developing economy characterized by institutional voids and uneven digital infrastructure. Second, it employs a novel text analysis approach using a 120-keyword framework adapted from Zareie et al. (2024), offering a granular, disclosure-based measure of digital transformation. This approach moves beyond traditional binary proxies or self-reported metrics, enabling a more precise assessment of how digital discourse manifests in corporate reports. Third, it situates the analysis within the COVID-19 crisis period, allowing for temporal segmentation and exploration of how digital strategies evolved under economic stress. These elements position the study to extend existing theories and empirical insights beyond developed market contexts.

Indonesia was selected as the empirical setting for three primary reasons. First, although similarly classified as a developing country, Indonesia's digital infrastructure significantly lags behind that of China and other regional peers. According to the Global Innovation Index (WIPO, 2021), Indonesia ranks 80th overall and 84th in ICT access, compared to China's 34th in ICT development. This disparity reflects broader systemic issues, including regulatory fragmentation, infrastructure gaps, and limited digital literacy (World Population Review, 2021). These institutional voids create a fertile environment for extending the RBV and DC theories by examining how companies in constrained settings adapt digital resources to support sustainability goals.

Second, despite these limitations, Indonesia holds an increasingly influential position in Southeast Asia's digital economy, which is projected to reach USD 109 billion by 2025 (Google et al., 2023). Its large, tech-oriented population—including 92% of knowledge workers who reportedly use generative AI (Microsoft and LinkedIn, 2024)—demonstrates significant untapped potential and makes Indonesia a compelling context to explore how companies mobilize digital transformation to enhance sustainability performance. Third, Indonesia's combination of institutional constraints and digital acceleration offers a rich setting to examine how companies reconfigure limited capabilities under pressure. This duality—rapid digital growth amid infrastructural deficits—not only sharpens the empirical relevance of our research but also informs ongoing debates surrounding strategic adaptation and sustainability integration in developing markets.

To investigate this dynamic, we constructed a dataset comprising 255 firm-year observations from companies listed on the Indonesia Stock Exchange (IDX) between 2019 and 2023, with ESG performance indicators sourced from Thomson Reuters. Digital transformation was assessed through keyword frequencies in annual reports based on the expanded text analysis framework, while sustainability reports were employed for robustness checks. We employed fixed effects regression models to control for sectoral and temporal heterogeneity. This methodological approach allows for a nuanced assessment of how digital transformation interacts with sustainability performance within an underdeveloped institutional environment.

Consistent with the RBV and DC theory (Barney, 1991; Teece et al., 1997), the results show that digital transformation is positively associated with sustainability performance—but only during the COVID-19 period. This finding suggests that digital capabilities became more valuable under crisis conditions, when companies were compelled to rapidly reconfigure their operations. Environmental and social scores showed particularly strong associations, reflecting the role of technology in improving operational efficiency, reducing emissions, enhancing transparency, and facilitating stakeholder engagement. Conversely, governance performance did not show a significant relationship, likely due to the inherently gradual and institutional nature of organizational change. To address potential endogeneity, we employed both Coarsened Exact Matching (CEM) and Heckman's two-stage model. Both tests confirmed the robustness of our main findings across different model specifications and time periods.

This study contributes to both theory and practice in several important ways. Theoretically, it refines the RBV and DC frameworks by showing that digital transformation can act as a contingent strategic asset, as suggested by Wang et al. (2023)—with its benefits becoming most salient under systemic shocks and institutional constraints (Gaspar et al., 2024). Practically, companies in environmentally intensive sectors can adopt digital tools for monitoring and managing emissions, while those in consumer and financial sectors may leverage digital interfaces to strengthen stakeholder engagement. Policymakers can also promote targeted digital adoption by investing in infrastructure and creating sector-specific incentives that align with ESG priorities, with Indonesia's sustainable development goals. This empirical evidence echoes the sustainability theoretical framework proposed by Suhardjo et al. (2024b), introduces a technological pillar as a crucial additional pillar of sustainability.

The remainder of this study is structured as follows: Section 2 provides a comprehensive literature review and develops research hypotheses. Section 3 outlines the research methodology. Section 4 presents empirical results and discusses their implications. Finally, Section 5 concludes the study by summarizing the key findings, discussing both theoretical and practical implications, and identifying limitations to be addressed in future research.

The RBV theory posits that a company's competitive advantages stem from its ability to leverage value, rarity, inimitability, and non-substitutability (VRIN) resources (Barney, 1991). This theory emphasizes the firm’s internal attributes as critical drivers of success (Hart, 1995). In the context of digital transformation and sustainability performance, RBV provides a lens through which companies can be understood to leverage their digital capabilities to create sustainable competitive advantages (Wei and Zheng, 2024). By developing unique digital competencies and innovative solutions, companies can enhance their operational efficiency, reduce environmental impacts, and improve social performance (Ding et al., 2024; Lu et al., 2024).

While RBV provides a strong foundational framework for analyzing how digital transformation drives competitiveness, it does not fully capture the perspective of rapidly dynamic environments (Korankye et al., 2025). In the face of uncertainty, companies have to adapt and respond quickly to maintain business stability and sustainability. As an extension of RBV, the DC theory underscores the importance of a company’s ability to integrate, cultivate, and reconfigure its resources and capabilities in response to external changes (Teece et al., 1997). Company that has dynamic capabilities can maintain its competitive advantage by actively modifying and upgrading as necessary in the amidst of volatile conditions (Zhang et al., 2022). In the context of this study, DC theory is especially relevant to explain how companies reconfigure their internal attributes, particularly in a developing country with an underdeveloped digital infrastructure.

However, critics have argued that RBV tends to assume relative resource stability and underplays the significance of environmental volatility (Peteraf and Barney, 2003). In contrast, Winter (2003) and Eisenhardt and Martin (2000) emphasize that dynamic capabilities are often evolutionary and path-dependent, particularly in resource-constrained environments—making their inclusion essential for analyzing companies' behavior in developing country contexts.

Prior studies have predominantly examined the relationship between digital transformation and sustainability performance within technologically advanced contexts. For example, Mormile et al. (2025) explored how Italian high-growth start-ups deploy advanced VRIN resources to address ESG challenges. Li (2022), using survey data from Chinese companies, identified an inverse U-shaped relationship between digital transformation and environmental performance. Similarly, Liu et al. (2024) and Chen and Ren (2025) found that digital initiatives positively influence ESG performance, particularly in the environmental and social dimensions. In Ghana, Korankye et al. (2025) showed that digital transformation among multinational companies enhances sustainability practices and regulatory compliance.

Despite this growing body of literature, Gomez-Trujillo and Gonzalez-Perez (2022) noted that the field remains largely conceptual and qualitative. In their review of 75 studies, only six employed quantitative methods—most relying on surveys rather than disclosure-based indicators. Consequently, there is limited empirical evidence from developing countries using archival approaches to capture actual implementation rather than organizational intention.

For instance, Gomez-Trujillo and Gonzalez-Perez (2022) highlighted the lack of contextual sensitivity in ESG measurement frameworks, while Korankye et al. (2025) emphasized methodological limitations in capturing digital signals. Our study responds to these gaps by applying a broader keyword taxonomy and focusing on Indonesia's unique regulatory and infrastructural landscape. This approach contributes to literature by advancing context-aware and methodologically diverse ESG research in underexplored settings.

Digital transformation has been shown to enhance sustainability performance across ESG dimensions. In environmental terms, digital tools enable real-time monitoring, optimize resource use, and facilitate clean energy adoption (Ding et al., 2024; Lu et al., 2024). On the social front, digital transformation improves responsiveness to stakeholder needs, promotes transparency, and creates safer, more inclusive workplaces (Camaréna, 2020; Chen and Hao, 2022; Lu et al., 2024; Vial, 2019). From a governance perspective, digitalization supports internal control systems, reduces information asymmetry, and promotes ethical decision-making (Chen and Zhang, 2024).

However, these benefits are not automatic. Digital transformation demands long-term investment and organizational restructuring (Li, 2022; Wu et al., 2023; Yang et al., 2024). In some cases, excessive investment in digital initiatives may divert attention from core sustainability responsibilities, potentially undermining sustainability outcomes (Wang and Hou, 2024). These trade-offs highlight the need for contextualized research, particularly in emerging economies where digital infrastructure and institutional readiness vary widely.

While prior studies have emphasized intentions or self-reported readiness, our study leverages company disclosures to offer a more grounded and objective assessment of digital engagement. By focusing on Indonesia, a digitally dynamic yet infrastructurally constrained economy, this study explores how companies navigate these complexities in practice. Based on this analysis, we propose the following hypothesis.

This quantitative study utilized secondary data obtained from Thomson Reuters, along with annual and sustainability reports of Indonesian publicly listed companies from the period 2019 to 2023. The initial sample included 340 firm-year observations. To ensure ESG data consistency, companies lacking sustainability reports were excluded, resulting in a final sample of 255 firm-year observations (Table 1). While digital transformation was measured using annual reports, sustainability performance is best interpreted when sustainability disclosures are available—particularly in light of Indonesia's shift from standalone sustainability reports (2019–2020) to integrated disclosures in annual reports (2021–2022) (IFAC et al., 2024).

To maintain robustness, all continuous variables were winsorized at the 1st and 99th percentiles. The regression model incorporates industry and year fixed effects to control for sectoral and temporal heterogeneity. Fixed effects were preferred over random effects due to the likely correlation between firm-specific attributes and explanatory variables. Although the sample size may appear modest, it is comparable to ESG-focused studies in emerging markets (Primacintya and Kusuma, 2025). Additionally Jenkins and Quintana-Ascencio (2020) suggested a minimum sample size of 25 is sufficient for regression analysis. Therefore, our sample of 255 firm-years is statistically adequate for the complexity of our model, particularly given the inclusion of multiple control variables and robustness tests.

Table 2 provides a breakdown of the sample per sector and year between 2019 and 2023.

This study utilized ESG scores from Thomson Reuters as a proxy for sustainability performance. Thomson Reuters is a well-established provider of both financial and non-financial data, including comprehensive ESG assessments (Alareeni and Hamdan, 2020). Their methodology evaluates over 700 companies worldwide across 10 sustainability indicators and is widely recognized for its rigor and transparency. By accounting for company size and disclosure transparency, Thomson Reuters aims to minimize biases in its ESG scores (Thomson Reuters, 2017).

Digital transformation is measured by text analysis from annual reports as the primary source due to their strategic relevance (Sui, 2024), with sustainability reports included for robustness checks. The measurement involves three steps: First, a collection of 120 digital transformation-related keywords (see Table 3) were compiled from recent literature (Chen and Srinivasan, 2024; Huang et al., 2023; Li et al., 2023; Teng et al., 2022; Zareie et al., 2024; Zhang and Zhao, 2023; Zhong and Ren, 2023). The keyword transformation process involved aggregating digital-related terms from annual and sustainability reports. We validated the keyword set through manual coding and cross-referencing with industry glossaries. Robustness checks included alternative keyword groupings and exclusion of boilerplate phrases to ensure construct validity. Second, the keywords were extracted from annual and sustainability reports through Python and obtain the total word frequency. Third, the normalization using logarithmic scaling applied to keyword frequencies to reduce skewness (Ding et al., 2024). The resulting values serve as a proxy for the extent of digital transformation within each company.

Several control variables were incorporated into the regression analysis to account for potential biases (Arayssi et al., 2020; Chen and Zhang, 2024; Ding et al., 2024; Luo et al., 2024; Zhang et al., 2024). These variables included company-specific characteristics (Tobin's Q (TOBINSQ), leverage (LEV), firm size (FSIZE), and firm age (FAGE)), as well as governance-related attributes (state ownership (STATEOWN), affiliation with a Big 4 public accounting firm (BIG4), and board size (BSIZE)). Table 4 provides detailed definitions of all the variables used in the study.

We employed STATA 17 to conduct Ordinary Least Squares (OLS) regression analysis to assess the association of digital transformation and sustainability performance. The following regression equation was used:

where i represents the company, t denotes the year, the dependent variable is ESG, and the key independent variable is DTAR (Digital Transformation). Control variables include TOBINSQ, LEV, FSIZE, FAGE, BSIZE, BIG4, and STATEOWN. As the panel data encompass various industries and year periods, the fixed effects are included in the model to minimize heterogeneity issues (Petersen, 2009).

Table 5 presents the descriptive statistics for all variables. The average ESG score is 53.528, positioning Indonesian companies in the mid-performance category according to Thomson Reuters standards, indicating moderate adoption of sustainability practices. Considering that an “A+” rating corresponds to scores above 92, this average reflects considerable room for advancement. The high variability (SD = 18.607) indicates significant variation in ESG implementation across sectors. Similarly, the digital transformation mean score of 2.196, while comparable to early-stage adopters in peer countries, trails behind benchmarks like China (mean = 2.842) (Li et al., 2024)—highlighting Indonesia's evolving but nascent digital maturity.

Table 6 and 7 presents the correlation analysis. The Pearson's correlation coefficient of digital transformation and sustainability performance at the 5% significance level. Similarly, most of the control variables have a significant correlations with sustainability performance. The correlation coefficients were below the threshold of 0.7, suggesting that multicollinearity is not a concern in this model (Kennedy, 2003).

Table 8 presents the results of the regression analysis, demonstrating a positive association between digital transformation and sustainability performance. In column 1, digital transformation is associated with sustainability performance at the 10% significance level. Upon incorporating fixed effects in column 2, the association becomes highly significant at the 1% level, demonstrating the robustness of this relationship. These results support Hypothesis 1 (H1) and align with previous research in the technology advancement country (Luo et al., 2024; Zhang et al., 2024), also in a developing country (Korankye et al., 2025).

This study suggests that companies actively engaging in digital transformation tend to have higher levels of sustainability performance (Chen and Ren, 2025; Liu et al., 2024). However, digital transformation in a resource-constrained environment is often hindered by underdeveloped digital infrastructure, regulatory uncertainty, and limited digital literacy (Sarpong et al., 2023). Viewed through the lens of RBV and DC theory, companies need to develop and reconfigure their capabilities to respond to these constraints (Teece et al., 1997). Companies can adjust the digital transformation at varying paces, tailored to their specific capabilities and resources (Sun et al., 2024; Verhoef et al., 2021). For instance, companies do not adopt large-scale digital transformation, but adopt incrementally and resource-efficient digital strategies that aligns with sustainability outcomes (Alessa et al., 2024; Korankye et al., 2025).

Interestingly, the positive relationship identified in our regression mirrors findings from studies in developed contexts. This alignment may be attributed to converging organizational behaviors during periods of systemic disruption—such as the COVID-19 pandemic—which compelled both developed and developing market companies to accelerate technology adoption to ensure operational continuity and resilience, irrespective of digital maturity.

To address potential endogeneity bias, this study employed Coarsened Exact Matching (CEM) regression and Heckman's two-stage model. CEM is a technique that ensures groups being compared have similar characteristics, thereby reducing sample selection bias (Blackwell et al., 2009). The sample was divided into treatment and control groups based on the median value of digital transformation. The results of the CEM regression analysis, presented in Table 9, support the findings of the primary regression, indicating that digital transformation is significantly associated with ESG scores, even when comparing similar groups. This finding suggests that the relationship between digital transformation and sustainability performance is robust and not solely driven by unobserved factors.

To further address the potential impact of unobserved variables on the relationship between digital transformation and sustainability performance, a Heckman two-stage regression was conducted. In the first stage, the average digital transformation score (AVEDTAR) served as an instrumental variable to predict companies’ likelihood of engaging in digital transformation. This choice is grounded in the assumption that industry-level diffusion trends—rather than firm-level capabilities alone—influence digital adoption. AVEDTAR captures these sectoral norms while remaining exogenous to firm-specific ESG outcomes, thus satisfying the exclusion restriction for valid instrumentation.

A dummy variable representing digital transformation (dDigital) was constructed based on industry and year. A value of 1 was assigned if the company’s digital transformation score (DTAR) was above the mean and 0 otherwise. In the second stage, the relationship between digital transformation and sustainability performance was estimated, accounting for potential selection bias.

Table 10 presents the results of the Heckman two-stage regression analysis. In the first-stage probit model indicates a significant positive relationship between the average value of digital transformation and the probability of adopting digital transformation at the 1% level. In the second-stage regression, the coefficient for digital transformation and sustainability performance remained significantly positive, even after controlling for potential endogeneity bias. This result suggests that the initial findings are robust and not driven by an omitted variable bias.

This study conducted three additional analyses to further investigate the relationship between digital transformation and company sustainability performance, proxied by ESG scores.

To delve deeper, this study examined the relationship between digital transformation and the individual ESG sub-dimensions: environmental, social, and governance (see Table 11). The results revealed significant positive associations with both environmental and social performance. This finding suggests that these dimensions are more immediately aligned with digital initiatives. Companies undertaking digital transformation tend to reduce energy dependency and improve environmental outcomes. On the social front, digital tools enhance stakeholder communication, transparency, and responsiveness, thereby reinforcing social responsibility (Yang et al., 2024).

The statistical insignificance of the governance dimension may reflect the time-lagged nature of structural reforms, which are inherently less responsive to short-term digital initiatives. Governance encompasses deeply embedded systems—such as internal controls, ethical practices, and oversight mechanisms—that typically require sustained institutional engagement and cultural adaptation rather than technological upgrades (Mormile et al., 2025). Unlike environmental and social disclosures, which tend to benefit more immediately from digital transformation, governance improvements often unfold gradually. This aligns with the concept of time-lagged dynamic capabilities (Wang et al., 2023), wherein organizational shifts become observable only after extended periods of resource commitment and strategic recalibration. Our findings suggest that while digitalization can catalyze transparency in certain ESG domains, governance practices may remain inert without deeper regulatory or cultural shifts.

This study further explored how the relationship between digital transformation and sustainability performance varies across three distinct economic periods: pre-COVID-19 (2019), during COVID-19 (2020–2022), and post-COVID-19 (2023). As shown in Table 12, a statistically significant positive association was observed only during the pandemic period. The crisis accelerated digital initiatives as companies sought to maintain operations amidst disruption and uncertainty (Kutnjak, 2021). Many strengthened digital capabilities for managing workflow, remote work, and operational resilience (Kronblad and Pregmark, 2024).

From the RBV perspective, digital transformation functioned as a strategic resource that enabled business continuity aligned with sustainability outcomes. Remote work, for instance, reduced physical interaction and supported health protocols (Nagel, 2020), while digital platforms enhanced environmental monitoring, stakeholder communication, and even governance oversight (Li et al., 2024). These mechanisms are associated with higher ESG performance during crisis conditions.

In contrast, no significant association was found in the pre- or post-COVID-19 periods. Prior to the pandemic, companies may have lacked urgency or strategic alignment to fully adopt digital initiatives (Kotter, 2008). Post-pandemic, many scaled back remote operations due to cost constraints or cultural inertia, undermining long-term integration (Peter et al., 2024). These findings suggest that digital transformation's effectiveness is shaped not only by technological investment, but also by contextual urgency and organizational readiness.

Papoutsi and Sodhi (2020) argued that sustainability reports are strong indicators of a company's actual sustainability performance. These reports provide stakeholders with information about the economic, environmental, and social impacts of corporate activities. Building on this notion, we modified the digital transformation proxy based on sustainability reports analysis (DTSR) to capture digital initiatives in the context of corporate sustainability strategies.

As shown in Table 13, the results indicated a statistically significant and positive correlation between digital transformation and ESG scores at the 1% level, further supporting the robustness of the findings in main analysis. Companies leveraging digital technologies tend to have higher sustainability performance (Wei and Zheng, 2024). These technologies enable firms to respond effectively to market changes, develop innovative business models (Jardak and Hamad, 2022), improve resource efficiency (Zhang et al., 2024), and facilitates better communication and transparency (Yang et al., 2023), all of which are commonly linked to sustainability performance.

This study investigated the relationship between digital transformation and sustainability performance by analyzing 255 firm-year observations of Indonesian listed companies between 2019 and 2023. Using text analysis on annual reports, we examined how digital practices are reflected in corporate disclosures. Indonesia's unique context as a digitally dynamic yet infrastructurally constrained emerging market, offering an insightful lens into how digital capabilities are mobilized as strategic resources. The study's design also incorporated time segmentation across pre-, during, and post-COVID-19 periods to assess temporal shifts in this relationship.

Our findings indicate that digital transformation is positively associated with sustainability performance—but only during the COVID-19 period. This suggests that in times of systemic disruptions, companies may accelerate digital initiatives to maintain continuity and stakeholder engagement. The strongest effects were observed in the environmental and social dimensions of ESG, likely due to improved efficiency, transparency, and responsiveness. The governance dimension showed no significant relationship, possibly reflecting the time-lag required for structural and cultural changes to materialize. These results underscore the conditional nature of digital transformation's benefits.

Theoretically, this study refines the resource-based view (RBV) and dynamic capabilities (DC) theories by demonstrating that digital transformation can function as a contingent strategic asset. Its influence becomes particularly salient when firms are compelled to reconfigure resources under pressure—such as during crisis periods—highlighting the importance of institutional context and temporal urgency. Our findings extend RBV by showing that the value of digital infrastructure is amplified under conditions of volatility, where its strategic utility depends not only on possession but on deployment. This complements DC theory, suggesting that firms with agile digital capabilities were better equipped to adapt ESG practices during COVID-19. The Indonesian context, marked by regulatory flux and infrastructural gaps, underscores the importance of context-specific capability orchestration and the need for adaptive strategies in emerging markets.

Practically, the study highlights the importance of aligning digital investments with sector-specific sustainability priorities. For instance, high-emission industries may benefit from automation and monitoring tools to enhance environmental compliance, while consumer-facing sectors may prioritize digital stakeholder engagement to strengthen social performance. These insights offer actionable guidance for firms seeking to leverage digital transformation not as a generic upgrade, but as a tailored enabler of ESG outcomes under varying institutional and operational conditions.

Sector-specific insights reveal that companies in high-emission industries (e.g. energy, manufacturing) benefited from digital monitoring tools that enhanced environmental reporting. Meanwhile, consumer-facing sectors leveraged digital stakeholder platforms to improve social engagement metrics. These findings suggest that policy interventions should be tailored to sectoral ESG priorities, with incentives for digital adoption aligned to disclosure maturity.

Finally, this study underscores the need for targeted infrastructure investment and policy support to enable meaningful digital adoption. In emerging markets like Indonesia, governments can play a catalytic role by creating incentive structures that align digital innovation with national sustainability objectives. Sector-specific strategies—tailored to the unique ESG priorities of industries—will be essential for maximizing both social impact and competitive advantage in the digital era.

Several limitations of this study warrant discussion. First, the absence of digital strategy analysis is a potential limitation. Future research should explore the combined impact of digital transformation and digital strategy on ESG performance. Second, the reliance on Thomson Reuters ESG scores as the sole measure of sustainability performance may limit the generalizability of the findings. Future studies could consider using multiple ESG data providers, such as MSCI and Sustainalytics, to obtain a more comprehensive assessment of sustainability performance.

In addition, further research should explore the mechanisms through which digital transformation influences sustainability performance. For instance, exploring the impact of digital technologies on supply chain sustainability, employee well-being and engagement, and green product innovation could provide valuable insights. Additionally, comparative studies examining the differences in digital transformation and sustainability practices across various countries and industries could offer valuable cross-cultural perspectives, enriching the theoretical and empirical discourse on this topic.