As carbon neutrality has become a central goal of global climate governance, how firms achieve low-carbon transformation has emerged as a critical research issue. However, prior studies have primarily focused on macro- or industry-level analyses, offering limited and fragmented insights into how digital technologies—particularly AI—affect firm-level carbon-neutrality performance and the underlying process-based mechanisms. To address this gap, this study adopts Resource Orchestration Theory (ROT) as the core analytical framework to examine how AI application is translated into firms' carbon-neutrality performance and integrates Dynamic Capability Theory (DCT) and Resource Dependence Theory (RDT) as complementary perspectives—used to explain internal capability reconfiguration and the role of the external resource environment, respectively—thereby constructing a comprehensive analytical framework. Using panel data of Chinese A-share listed manufacturing firms from 2018 to 2023, this study conducts empirical analysis based on a two-way fixed effects model. The results indicate that AI application significantly enhances firms' carbon-neutrality performance, and this finding remains robust after a series of robustness checks and controls for potential endogeneity. Further analyses reveal that AI exerts its effects primarily through alleviating financing constraints, enhancing R&D vitality, and increasing green patent outputs. Moreover, green technological efficiency, which reflects firms' internal capabilities, and the level of green finance development, which captures the external resource environment, both exhibit significant positive moderating effects on the focal relationship. From the perspective of ROT, this study reexamines the environmental value of AI, demonstrating that such value does not stem solely from the technology itself but is shaped through managerial resource orchestration processes and the interaction between internal capabilities and external resource environments. By moving beyond the conventional view that attributes AI's environmental effects to mere technological inputs, this study extends the literature through a process-based perspective. In the context of concurrent digital and green transformations, this research provides important theoretical insights and empirical evidence for understanding low-carbon development among firms in emerging economies.

Amidst burgeoning interest in sustainability and corporate value, this study addresses an empirical gap in the ASEAN-6 markets (Indonesia, Malaysia, Singapore, Philippines, Thailand, and Vietnam) by investigating the interplay between green innovation capability (GIC), environmental, social, and governance ratings (ESGR), energy transition (ETR), and firm value (FV). It further explores how ESGR and ETR moderate the GIC–FV relationship. Using Generalized Method of Moments (GMM) regression, we analyzed panel data from Refinitiv Eikon for 2806 companies across the region from 2020 to 2024 (14,030 firm-year observations). Findings reveal novel insights specific to ASEAN-6; GIC and ESGR significantly enhance FV, confirming their strategic importance. However, the pathway to increased FV through sustainability is neither straightforward nor uniform but a multidimensional phenomenon. The findings reveal that while GIC and ESGR significantly enhance FV, confirming their strategic importance, the pathway to value creation is neither straightforward nor uniform. Instead, the impact of these sustainability factors is profoundly shaped by country-specific characteristics and intricate interactions among variables. Practically, this study underscores the necessity for managers to formulate sustainability strategies that leverage GIC and ESGR. Furthermore, it offers guidance for policymakers to design tailored, context-specific frameworks within each ASEAN-6 nation. By illuminating the context-dependent nature of these relationships, this research fills a critical empirical void in understanding how sustainability dimensions influence FV in key emerging economies.

Corporate digital transformation influences not only internal business processes and strategic management models, but also the way the stakeholders engage in corporate sustainable development. We explore the impacts of corporate digital transformation on stakeholder green engagement at three levels of stakeholders, inner-layer, mid-layer, and outer-layer stakeholders, as well as the moderating effect of digitalization depth and breadth. Based on stakeholder theory and stakeholder stratification perspective, we find that corporate digital transformation significantly improves stakeholder green engagement in different ways: it improves green investment efficiency for inner-layer stakeholders, enhances green disclosure quality for mid-layer stakeholders, and strengthens responsiveness to green policies for outer-layer stakeholders. Besides, the impact of digitalization is asymmetric: depth enhances engagement through integration of capabilities, whereas breadth undermines engagement through the dispersion of resources and organizational complexity. The significance of these findings is that they combine the stakeholder stratification theory with the digitalization studies and contain the realistic advice that managers and policymakers can use when implementing digital technologies to organize diverse stakeholders in order to promote sustainable corporate performance.

Artificial intelligence (AI) reflects a paradox for corporate sustainability: it provides tools for genuine socio-economic improvement and enables greenwashing at scale. This study examines this duality in emerging Asian markets, where rapid AI adoption coincides with evolving regulatory regimes. Using a panel of 1260 firm-years across six economies, we construct a firm-level green washing index and estimate panel models with Mondale corrections. The results show that AI adoption is positively associated with green washing intensity. Crucially, this risk is disciplined by two forces: verified ESG performance and regulatory stringency. We demonstrate their complementarity; the disciplining effect of verification is substantially stronger where regulatory enforcement is credible. Furthermore, firm valuation rewards verified ESG performance, not AI adoption itself. These findings reframe verification and regulation as synergistic rather than independent safeguards, advancing theory on disclosure credibility. They also provide actionable insights for policymakers designing governance regimes and for investors seeking to distinguish substantive sustainability from AI-enabled impression management.

Drawing on the resource-based view (RBV), this study examines how green intellectual capital (GIC) enhances organizational resilience (OR) among hospitality SMEs in Egypt. It analyzes the roles of green entrepreneurial orientation (GEO), green dynamic capability (GDC), green absorptive capacity (GAC), and green competitive advantage (GCA) in converting green intangible resources into resilience outcomes. Data from 239 SME hotel managers were analyzed using PLS-SEM with SmartPLS 4 to test direct, mediating, sequential, and moderating effects. Results indicate that GIC positively influences GEO, GDC, and GCA. GEO and GDC mediate the GIC–GCA relationship, while GCA significantly strengthens OR. A significant sequential mediation pathway links GIC to OR through GEO, GDC, and GCA. Moreover, GAC positively moderates the effects of GIC on GEO and GDC. The study extends RBV by integrating green capability configurations as boundary conditions and provides insights for enhancing resilience and competitiveness in hospitality SME markets.

In an era of growing stakeholder pressure and regulatory fragmentation across global jurisdictions, the quality of environmental, social and governance (ESG) reporting has become foundational to corporate valuation, investment screening and regulatory oversight. This study uses machine learning (ML) techniques to predict global reporting quality and examine how the determinants differ in disclosure quality in developed and emerging economies as well as civil and common law jurisdictions. Drawing on a cross-sectional sample of 5000 publicly listed companies across 50 countries for the fiscal year 2022, we develop and evaluate Random Forest and XGBoost models alongside a panel regression benchmark, using financial performance metrics, corporate governance indicators and institutional characteristics as predictors. The primary contribution of this study is methodological: The authors demonstrate that ML techniques deliver superior predictive power compared to traditional econometric approaches by capturing the non-linear, high-dimensional interactions that characterise ESG disclosure decisions globally—a capacity that conventional ordinary least squares and fixed-effects regressions structurally cannot replicate. The study integrates signalling theory, legitimacy theory and agency theory to explain corporate disclosure motivations across diverse institutional settings. The results show that agency theory, in particular, illuminates why board size and board independence consistently emerge as strong predictors, since independent monitoring reduces information asymmetry and incentivises management to commit to transparent sustainability disclosures. Results confirm the superiority of ML techniques, with XGBoost achieving a test R ² of 0.78 compared to 0.62 for panel regression. SHapley Additive exPlanations (SHAP) analysis identifies firm size, governance score and board independence as the most consequential predictors. Board independence exhibits a threshold effect: ESG quality gains plateau beyond approximately 65%–70% independent directors. The study offers actionable insights for investors and regulators seeking to identify firms at high risk of greenwashing through governance-marker profiling and sustainability officers benchmarking their organisations' reporting quality against global peers.

This paper examines the association between biodiversity disclosure, artificial intelligence (AI), and gender diversity of board and the cost of capital in Chinese A-listed companies. Global sustainability and long-term business resilience increasingly rely on biodiversity protection and technological adoption, yet the financial aspects of these issues are under-researched. Based on agency theory and stakeholder accountability models, we hypothesise that biodiversity disclosure and AI adoption will lead to lower financing costs through better governance, transparency and reduced risk. Moreover, we hypothesise that board gender diversity enhances these effects by enhancing monitoring, oversight and credibility of sustainability initiatives. Based on large-scale firm-level data (2010–2024) from CSMAR and the Shenzhen Stock Exchange, our results indicate that biodiversity disclosure and AI integration have a significant positive effect on the weighted average cost of capital, cost of equity, and cost of debt for Chinese A-share-listed firms. In addition, gender diversity is a moderator that enhances the cost-reducing impacts of biodiversity disclosure and AI adoption. Artificial intelligence can be used to reduce a firm's financing costs by improving information processing, minimising uncertainty, and enhancing the credibility of its disclosures. AI technologies can analyse massive amounts of financial and operational data quickly and with high precision. This enables firms to provide more transparent and believable information to investors and lenders, thereby alleviating information asymmetry between firms and their capital providers. These results highlight the complementary role of governance, sustainability and technology in lowering financing costs. As the drivers align corporate finance with sustainable development objectives, policymakers and international regulators are urged to require biodiversity reporting, promote gender-diverse boards, and embrace AI-enabled transparency.

Integrating sustainability not only into corporate strategy and product design is essential to address pressing global challenges. This study proposes a framework that integrates social life cycle assessment (S-LCA) into time-driven activity-based costing (TD-ABC) to manage both social and economic issues by assessing social impacts across value chains. An illustrative case study in the packaging sector demonstrates the model's (TD-ABC-S-LCA) feasibility in calculating the direct and indirect upstream social impacts of a company. Significant social risks can be identified in non-recycled paper packaging due to the sourcing of resources from high-risk regions. Contribution and geographical variability analysis identify opportunities, such as strengthening supplier relationships and optimizing material sourcing. Despite limitations, including reliance on generic databases and a cradle-to-gate scope, this framework provides a practical method for companies to align economic goals with social responsibilities. It advances sustainability accounting practices, paving the way for further research and business applications.

Green bonds play a central role in sustainable finance, yet concerns about greenwashing raise questions about the credibility of issuers' sustainability disclosures. Using dictionary-based methods and domain-specific BERT transformer models, this paper proposes two greenwashing alert metrics and investigates their performance by analyzing sustainability reports of European corporate green bond issuers from 2019 to 2023. First, we develop the SDGs Omission Index (SDGOI), which measures the discrepancy between Sustainable Development Goals (SDGs) declared ex-ante in green bond frameworks and those subsequently reported in sustainability disclosures. We show that the use of SDG-specific language is associated with broader SDG coverage, whereas generic environmental language is not. Second, we introduce the Environmental Sentiment Metric (ESM), capturing opportunity-oriented environmental sentiment. We find that a more opportunity-oriented tone is positively related to SDG omission, ESG controversies, and greenwashing accusations. Together, SDGOI and ESM provide interpretable, disclosure-based indicators that can support issuing greenwashing alerts in the European green bond market.

Responsible consumption and production, emphasized in Sustainable Development Goal 12 (SDG 12), require both company-level sustainability initiatives and an understanding of how consumers respond to corporate responsibility signals. Environmental, Social, and Governance (ESG) framework has become a central mechanism through which companies communicate their commitment to sustainable development; however, the behavioral pathways that link ESG perceptions with consumer behavior remain under-researched. This study examines how consumers' perceptions of companies' ESG engagement shape sustainable consumption through the mechanisms proposed by the Theory of Planned Behavior (TPB). Using survey data from a nationwide sample of 1000 consumers across four generational cohorts, the model is tested with partial least squares structural equation modeling and multigroup analysis. The results indicate that perceived ESG engagement acts as a structured antecedent that influences attitudes, subjective norms, and perceived behavioral control, which subsequently shape behavioral intention and actual sustainable consumption. Attitudes emerge as the dominant mechanism, indicating that ESG-aligned consumption is largely value-driven, while normative and control-related factors play complementary roles. Although behavioral intention significantly predicts actual behavior, an intention–behavior gap remains. Generational differences are limited and mainly concern the translation of intention into behavior. By integrating ESG into TPB, the study provides a behavioral micro-level explanation of how company-level ESG engagement supports the objectives of SDG 12.

We investigate how traditional capital structure choices interact with emerging strategic drivers—ESG performance, R&D intensity, digitalization, and board gender diversity—to shape firm profitability in Saudi Arabia during the Vision 2030 reform era. Using a fixed-effects panel regression model on 2067 firm-year observations (2018–2024), we find that traditional leverage metrics show no consistent direct impact on profitability, whereas R&D intensity emerges as the strongest positive determinant. ESG and digital transformation do not influence financial performance directly but enhance the effect of R&D and governance factors when treated as moderators. We contribute by integrating corporate finance and strategic management theories under the dynamic capabilities lens, highlighting the contingent role of institutional transformation in emerging economies, and offering a robust, multi-dimensional framework for strategic investment decision-making in transitional markets. These findings provide actionable implications for firms and policymakers working toward sustainable, innovation-led growth under reform agendas like Vision 2030.

This study analyses the commitment of marine tourism companies to Corporate Social Responsibility (CSR) and the factors that affect it (economics, pressures from interest groups, barriers, innovative capacity, relationships of the company with its environment and characteristics of the businesses). The data were collected in 2020 using a structured questionnaire, administered with in-depth interviews with business owners on the island of Fuerteventura (Canary Islands). Thirty-two small or micro-enterprises participated in the study, out of the 150 companies in the said sector. A questionnaire was designed for an in-depth interview with business owners. The data obtained are analysed through a combination of exploratory factor analysis and backward stepwise multiple linear regression, allowing the simultaneous examination of the interrelationships between several latent constructs derived from observable variables. The results indicate that the commitment of these companies to CSR is more conditioned by driving factors than by barriers, although one of the most important difficulties is the lack of trust in public administrations. The existing governance framework is considered limited, so it is necessary to involve all stakeholders in the tourist destination in promoting socially responsible actions. A portfolio of public policies is proposed to promote responsible behavior among companies in the sector.

Despite burgeoning literature on sustainable innovation, there is limited understanding of how adversarial conditions, such as competitive intensity and environmental threat, shape green product innovation and the underlying mechanisms of this relationship. To address this gap, a caravan passage model is proposed using the strategy tripod perspective. Utilizing second-generation econometric analysis and data from 2011 to 2024 across firms in the Middle East and North Africa (MENA) regions, we addressed endogeneity and reverse causality and estimated long-run relationships. We find evidence that while environmental threat does not directly influence green product performance (GPP), it enhances co-innovation capability, which in turn promotes GPP. On the other hand, competitive intensity, both directly and indirectly, drives GPP. However, the quantile results suggest a non-linear relationship. Finally, co-innovation capability is identified as a strategic medium to achieve green product performance. Managers must redirect focus from product innovation to green product performance as a more consequential outcome. Second, policymakers should reframe environmental threats as a catalyst for a green strategy. Finally, strategic collaboration is necessary to overcome adversity, and managers must move beyond a linear view of competition by adopting strategic differentiation and avoiding outspending rivals.

This study examines how engineering trained chief executive officers (CEOs) determine firms' sustainability performance and greenwashing behavior in Australian listed firms from 2016 to 2024. Drawing on Upper Echelons theory and Imprint theory, we argue that engineering cognition influences environmental strategy by providing conservative, evidence-based sustainability disclosures. We find that engineering CEOs are associated with weaker sustainability performance and lower greenwashing, indicating more credible and performance-based environmental disclosure. Sustainability assurance moderates this association by increasing external verification of sustainability disclosures, encouraging firms to follow compliance-oriented reporting practices and limiting CEOs' ability to influence disclosure credibility. Subsample analysis shows engineering CEOs are associated with stronger sustainability performance and an even greater reduction in greenwashing in technically intensive industries. Robustness tests using propensity score matching (PSM), entropy balancing, lagged models, and two-stage least squares (2SLS) confirm the consistency of our results. This study shows that engineering expertise influences sustainability performance, disclosure quality and greenwashing. The findings provide insights for boards, regulators, and stakeholders interested in credible sustainability strategies.

This paper examines the impact of corporate biodiversity risk exposure on investment and financing sensitivities to growth opportunities captured by Tobin q (Q). Using a sample of non-financial US listed firms over the period from 2001 to 2023, we find that biodiversity risk exposure is positively associated with investment sensitivity to Tobin's Q, suggesting that firms facing higher biodiversity risk respond more strongly to growth opportunities signaled by market valuations. This result indicates that biodiversity risk amplifies the informational content of Tobin's Q in guiding investment decisions. In addition, we find that biodiversity risk exposure increases equity financing sensitivity to internal cash flows, implying that firms adjust financing behavior in response to perceived risk conditions while still relying on internal resources to support growth opportunities. Our findings suggest that biodiversity risk plays an important role in shaping how firms interpret market signals and allocate capital. These results have important policy implications for regulators, investors, and managers by highlighting the value of integrating biodiversity risk into corporate disclosure frameworks and sustainable finance policies to enhance market transparency and capital allocation efficiency.

The Environmental, Social, and Governance (ESG)-performance literature has grown substantially, yet a fundamental question remains underexplored: do ESG investments improve firm performance, or do high-performing firms simply invest more in ESG? We empirically address this question using panel vector autoregression with Granger causality tests on Korean listed firms rated by the Korea Corporate Governance Service (2013–2021), examining disaggregated ESG components alongside both financial performance and innovation outcomes. After controlling for firm and year fixed effects, we find no evidence that ESG improvements predict subsequent profitability or innovation within firms. However, profitability significantly predicts subsequent Environmental ESG investment, consistent with organizational slack theory. These findings suggest that much of the observed ESG-performance association may reflect selection rather than causation. We discuss implications for the broader sustainability, CSR, and innovation literatures, arguing that the field should routinely test for reverse causality before drawing causal conclusions informing corporate strategy and public policy.

This paper investigates how board gender diversity relates to corporate social responsibility (CSR) performance in Thailand, where patriarchal and hierarchical cultural norms shape gender roles differently compared with Western economies. Drawing on theories from social psychology, we posit that Thailand's cultural norms weaken the positive relation between board gender diversity and CSR performance as well as the relation between female CEO leadership and CSR performance. Consistent with the predictions by Social Role Theory and Role Congruity Theory, the empirical results show that neither female board representation nor female CEO leadership alone is associated with CSR performance. In support of the Relational Identity Theory, moreover, a coalition of a female CEO and female directors is positively related to CSR performance. Robustness tests confirm that CSR performance positively relates to firm valuation. We conclude that a coalition of female leaders offers a powerful mechanism for advancing CSR practices in emerging markets where cultural norms constrain individual female leadership effectiveness.

Prior research has primarily examined corporate social responsibility (CSR) directed toward stakeholders such as investors, consumers, and regulators, signaling trustworthiness and positive moral character. However, nonmarket strategies such as CSR may also be interpreted by firms in relation to competitors, suggesting that CSR may influence interfirm competition. Despite the growing relevance of CSR in shaping competitive dynamics, we have only a limited understanding of how firms respond competitively to rivals' CSR activities. While CSR activities signal investments in specific stakeholders and a long-term orientation, we argue that a rival's CSR activities convey information about the strategic positioning that influences a focal firm's competitive actions. By utilizing signaling theory and the awareness-motivation-capability framework, we argue that a gap between a focal firm's CSR substantive activities and a rival's symbolic CSR activities jointly affects their competitive actions, depending on the CEO's motivational factors: regulatory focus and compensation structure. The longitudinal analysis of 4341 dyad-years from the S&P 500 companies suggests that larger CSR gaps within rival dyads increase their competitive dissimilarity. The interaction analysis reveals that this relationship depends on a CEO's prevention focus and performance-based compensation. This study enhances understanding of the signaling mechanism of CSR activities toward rivals and highlights the spillover of nonmarket strategies into competition-based strategies.

Italian listed enterprises increasingly rely on intellectual capital (IC) to enhance competitiveness and sustainability performance. As IC, comprising human, structural, and relational capital, is rarely recognised in financial statements due to the lack of standardised frameworks, its disclosure has gained relevance in sustainability reporting to address stakeholder expectations. Although prior studies acknowledge the compatibility between IC and sustainability reporting, limited attention has been paid to explicit gender and digital-related IC disclosure, particularly in relation to digital transformation. Drawing on legitimacy, resource-based view (RBV) and stakeholders' theories, this study examines digital and gender dimensions of IC disclosure in sustainability reports. Using content analysis of hand-collected data, it investigates Italian listed enterprises from 2020 to 2025. IC disclosure is measured through a weighted index across human, structural, and relational capital dimensions. The findings show a positive association between IC disclosure and ESG reporting, with firms disclosing digital elements of structural and relational capital, while gender issues remain concentrated in human capital.

Artificial intelligence (AI) is increasingly recognized as an effective tool in promoting corporate social responsibility (CSR) and sustainable governance. This study investigates how AI shapes corporate environmental information disclosure (EID), using panel data of Chinese A-share listed companies from 2013 to 2023. Employing a year and industry fixed effect model and a series of robustness checks, the findings reveal that AI adoption is associated with higher EID. Further analysis indicates this relationship is strengthened by dual internal mechanisms: green innovation and corporate governance. From the ability perspective, green innovation enhances firms' ability to generate and process environmental information. From the motivation perspective, corporate governance strengthens managerial incentives and makes firms more motivated to respond to stakeholders' environmental expectations. The positive association between AI and EID is also more pronounced in firms subject to stronger external monitoring, proxied by media attention and analyst attention. The findings clarify how AI adoption supports EID and offer practical guidance for enterprises and policymakers seeking to leverage AI, internal governance, and external oversight for green governance.

The rise of artificial intelligence (AI) presents both opportunities and challenges for corporate social responsibility (CSR), fundamentally altering how businesses address societal needs. Yet research at the CSR–AI interface remains fragmented. This study conducts a bibliometric analysis of 747 peer-reviewed articles, encompassing 39,435 references to uncover the intellectual structure of CSR-AI research. We address three key questions: the evolution of CSR-AI studies, current research hotspots, and future directions. Our findings reveal nine intellectual subdomains, with web accessibility and online platforms as dominant themes. The CSR-AI field has evolved through three growth stages, accelerating markedly in recent years, centering on sustainability, impact, and performance, while emerging frontiers focus on firm performance, co-creation, and environmental sustainability. By synthesizing dispersed knowledge and mapping key trajectories, this study offers a systematic foundation for understanding how AI is redefining responsible business. It concludes with seven research opportunities to guide CSR–AI scholarship and practice.

This study examines the maturity of supplier-related environmental disclosures in sustainability reports of top environmental, social, and governance (ESG)-performing Brazilian companies. A content analysis of 67 reports from firms listed on the Corporate Sustainability Index (CSI) was conducted using the CRITIC method to weight disclosure criteria and Grey Fixed Weight Clustering to classify maturity levels. Results reveal substantial variation: nearly 60% of firms fall into the low-maturity cluster, while companies in regulated or internationally scrutinized sectors, such as banking, pulp and paper, and food processing, demonstrate higher maturity. Findings highlight sectoral disparities, the influence of regulatory and market pressures, and gaps between stated sustainability goals and supplier accountability. The study advances debates on supply chain environmental accountability, offers a replicable framework for benchmarking disclosure maturity, and provides practical insights for managers, ESG analysts, and policymakers to strengthen transparency, due diligence, and alignment with sustainability commitments.

This study examines the relationship between humble leadership and employee deviance in uncertain organizational environments, with a focus on the moderating role of employee mindfulness and the mediating role of basic psychological needs, as framed by self-determination theory (SDT). Following a time-lagged approach, data were collected from public sector hospitals through a survey strategy. Subsequently, structural equation modeling (SEM) was employed to test the hypotheses. Results show how humble leadership can unintentionally increase employee deviant behavior in uncertain environments. However, employee mindfulness mitigates this effect and the satisfaction of basic psychological needs (autonomy, competence, and relatedness) significantly reduces deviant behavior. The findings underscore the importance of internal corporate social responsibility (CSR) practices in healthcare settings. Hospitals should focus on meeting the psychological needs of employees and provide mindfulness-based training to foster resilience and reduce deviance. Leaders should also recognize the contextual limitations of humility as a leadership style during crises. This study challenges the paradigm that predicts positive outcomes of leader humility, demonstrating its potential in increasing employee deviance.

ESG reporting is widespread, but symbolic commitments do not always reflect substantive practices. This study conducts a systematic literature review of 62 empirical articles published between 2021 and 2025 to synthesize the main determinants and consequences of this disclosure–performance misalignment in ESG reporting (commonly referred to as ESG decoupling). Following the SPAR-4-SLR protocol and applying the TCCM framework, the review organizes evidence across theories, contexts, characteristics, and methodological approaches. Drawing on systems theory and performance feedback logic, the study develops an integrative conceptual framework explaining how symbolic and substantive ESG practices interact over time. The framework identifies four recurring mechanism clusters—agency and governance, institutional and regulatory, information asymmetry and signaling, and resource and capability—that shape short-term tactical responses and longer-term structural misalignment. The review provides a coherent, theory-informed synthesis and offers structured insights for future research and for policymakers, managers, and investors concerned with the credibility of ESG reporting.

The present study develops a conceptual map that identifies and delineates the knowledge base underpinning the field of carbon leadership, especially focusing on analyzing the impact of transformational leadership on carbon sequestration performance as well as the potential mediating role of ESG integration in this relationship. Based on a combined approach of bibliometric analysis and systematic literature review, the paper examines the vast literature on the topic using different methods like keyword co-occurrence, bibliographic coupling, citations network analysis, and VOSviewer visualization. Also, the TCM synthesis method was used to summarize the existing research on the topic. In line with this methodology, the study reveals an extensive and continuously growing literature in the intersection of ESG, sustainability governance, and climate change strategies. However, despite the significant amount of research carried out in the area, the majority of studies concentrate their efforts on ESG disclosures and the financial performance of firms but not on climate-related variables such as carbon sequestration. Moreover, little attention is paid to studying leadership and other governance processes within the framework of research on ESG and carbon sequestration. This gap motivates the development of a research model that suggests transformational leadership as the main driver of ESG integration, thus fostering carbon sequestration performance. Integrating stakeholder theory, institutional theory, and resource-based view, this study contributes to the literature with a new approach that highlights the importance of leadership in sustainability transitions.

The relationship between board governance and corporate carbon emission disclosure remains persistently inconsistent across the empirical literature, despite decades of accumulated evidence. Drawing on agency, stakeholder, legitimacy, institutional, and upper echelons perspectives within a single analytical framework, we conduct a three-level meta-analysis with robust variance estimation to correct for within-study dependence, synthesising 66 studies and 140 effect sizes across diverse institutional contexts over 2010–2024 while explicitly modelling institutional and methodological boundary conditions. Environmental committees and gender diversity are the strongest predictors of carbon transparency, followed by board size and independence; CEO duality yields no significant aggregate effect. These pooled estimates, however, mask substantial contextual variation. Governance efficacy is strictly contingent on institutional setting: effects are markedly larger under mandatory reporting regimes than voluntary ones, are strongly attenuated in North American markets relative to Asia and Europe, and CEO duality undergoes a directional reversal—positive in common law systems and negative in civil law systems. Research design type and disclosure measurement framework account for a meaningful additional share of between-study variance. Internal board structures and external institutional pressures thus operate as mutually reinforcing rather than substitutive mechanisms—a finding that carries targeted, jurisdiction-specific implications for investors and regulators designing climate disclosure mandates.

Sustainable manufacturing transitions require companies to demonstrate not only environmental and economic benefits, but also measurable advances in corporate social responsibility (CSR). Therefore, we propose using a guideline-based Social Life Cycle Assessment (S-LCA) aligned with UNEP (2020) and ISO 14075 (2024) to evaluate the social performance of this transition in the case of introducing AI-assisted ultrashort-pulsed laser mould texturing in dishwasher manufacturing. The assessment covers 238 companies across the value chain and five stakeholder groups. Twenty subcategories were examined using conditional sensitivity analysis to capture context-specific changes, complemented by stakeholder weighting and pedigree matrix. Results suggest moderate improvements in social performance, primarily driven by enhanced occupational health and safety and improved consumer well-being. The aggregated score increases progressively across all scenarios, indicating a consistent positive trend in CSR-related performance under the assessment's assumptions. The findings suggest that S-LCA can support CSR evaluation in an advanced manufacturing context, contributing to managerial decision-making regarding the adoption of sustainable technologies.

With the advancement of the digital revolution, application scenarios are becoming increasingly complex and diverse. Accurately identifying technological opportunities (TOs) driven by user needs within these scenarios remains a significant challenge for enterprises, while existing theories and practices often lag behind. To address this gap, this study proposes a comprehensive framework for identifying and evaluating TOs based on scenario demands. The framework leverages text mining techniques to analyze scenario demands in depth and employs cosine similarity to quantify the extent to which these needs are satisfied. Additionally, generative topographic mapping (GTM) is used to construct patent maps, facilitating the identification of potential technological opportunities (PTOs). To evaluate the viability of transforming PTOs into actionable TOs, system dynamics (SD) simulations are applied to model sustainable business scenarios. The effectiveness of the framework is demonstrated through a case study on insulated gate bipolar transistors (IGBTs). Results indicate that the proposed approach enhances the accuracy of technological opportunity identification (TOI) and provides both theoretical and practical guidance for enterprises seeking to strategically align their technological development with evolving scenario demands.

Companies increasingly claim to adopt artificial intelligence (AI) not only for economic but also for ecological and social purposes. However, in light of rising greenwashing, bluewashing, and ethics washing, the impact of the communicated rationale on employees' initial attitude toward AI introduction remains unclear. Therefore, in a 3 × 2 between-subjects online vignette experiment with 426 German employees, we examined how the stated reason for AI adoption (ecological, social, economic) and the company trustworthiness (low, high) influence message credibility and employees' initial attitudes toward AI. Ecological and social rationales were perceived less credible. Company trustworthiness did not affect message credibility. Initial attitudes toward AI were significantly lower for social rationales rather than economic ones. Further, pro-environmental initial attitudes reduced the influence of message credibility on initial attitudes toward the AI for ecological sustainability—an effect we refer to as environmental wishful thinking. This study advances the understanding of employees' initial attitudes toward and the management of organizational adoption of AI for sustainability.

The bioeconomy transition risks underrepresenting social sustainability, while existing Social Life Cycle Assessment (S-LCA) applications remain insufficient for comparison and decision support due to heterogeneous and non-standardized selection of social impact categories. This study proposes a cross-regional baseline set of impact categories to improve comparability and decision support in bioeconomy S-LCA. A Fuzzy-Delphi approach was applied with 96 experts from Europe and Brazil representing science, industry, government, NGOs, and producers/workers. Experts evaluated 31 UNEP/SETAC social impact subcategories using Likert scales converted into triangular fuzzy numbers to determine consensus and inclusion thresholds. Results reveal clear regional differences in perceived priorities, yet nine categories were consistently selected across regions: Transparency, Access to material resources, Local employment, Supplier relationships, Equal opportunities/Discrimination, Health and safety, Public commitment to sustainability issues, Contribution to economic development, and Technology development. Sensitivity analysis confirms the robustness of this baseline under varying consensus parameters. The study provides a practical, participatory framework for selecting social indicators in bioeconomy S-LCA based on supply-chain geography, enabling more transparent, reproducible, and context-sensitive social assessment.

This paper examines whether occupational pension funds (OPFs) apply a strategic and long-term logic when assessing ESG practices in their investee firms. Using discourse analysis of semi-structured interviews with asset managers and workers' representatives, we examine whether Spanish OPFs look beyond compliance-driven CSR and consider the creation of social capital as a source of financial value. Our findings show that CSR is primarily interpreted as a reputational and regulatory risk-management tool, with engagement remaining mostly defensive and influenced by standardised reporting and short-term market pressures. Although some OPFs, particularly worker representatives, identify potential long-term benefits in more tailored approaches, investors display no consistent belief that social capital generation improves financial returns. Nevertheless, good governance, engagement, and higher-quality non-financial information emerge as potential enablers of value. Focusing on a socially pressured investor group, the study offers original insights into the motivations and limitations shaping ESG decision-making within the context of evolving European regulation.

Despite the strategic urgency of corporate sustainability, fostering employees' voluntary pro-environmental behavior at work (PEBW) remains a critical organizational challenge. Drawing on Social Information Processing (SIP) theory, this research explicates the psychological mechanisms linking coaching leadership to PEBW, positioning leadership as a proximal informational cue that shapes employees' role perceptions and self-definitions. We propose a comprehensive model wherein coaching leadership promotes PEBW through the sequential mediating roles of meaningfulness of work and organizational identification, while investigating corporate social responsibility (CSR) as a critical boundary condition. Employing a four-wave time-lagged research design with data collected from 415 South Korean employees, the findings reveal that coaching leadership exerts both a direct positive influence on PEBW and an indirect influence via the proposed attitudinal pathway. Specifically, the developmental signals provided by coaching leaders enhance employees' sense of meaningfulness, which is subsequently attributed to the organization, fostering a deep sense of organizational identification that drives discretionary environmental actions. Furthermore, the results confirm that CSR functions as a pivotal contextual filter. By bridging the micro-dynamics of developmental leadership with the macro-context of organizational ethics, this study establishes a high level of originality within the sustainability literature. The findings explicitly reveal that employees do not process leadership behaviors in a vacuum. Instead, macro-level moral frameworks, such as CSR, are absolute prerequisites to validate the authenticity of micro-level leadership interventions. Consequently, this research provides a groundbreaking perspective by proving that developmental leadership effectively cultivates identity-based ecological stewardship exclusively when anchored in a genuinely responsible corporate environment.

How to foster high-quality green innovation has become a critical question for firms pursuing sustainable transformation. Yet, it remains insufficiently understood whether and how ESG-related signals contribute to this process. Drawing on signaling theory, this study examines the effect of ESG performance, as an observable proxy for ESG signals, on green innovation quality using panel data from Chinese A-share listed firms during 2019–2024. The results show that ESG performance is positively associated with green innovation quality. The three ESG dimensions do not exert equal effects, with governance showing the strongest influence. Institutional ownership serves as an important signal interpretation mechanism through which ESG-related credibility is translated into higher-quality green innovation. Market competition further strengthens both the direct effect of ESG performance and the indirect effect transmitted through institutional ownership. Additional analyses indicate that these effects are more pronounced among growth-stage firms, firms in heavily polluting industries, and non-high-tech firms. The study extends the ESG-green innovation literature by shifting attention from innovation quantity to quality formation and enriches signaling theory by showing that the innovation consequences of ESG depend on investor interpretation and market context.

This study examines how generative artificial intelligence (GenAI) can strengthen transparency and sustainability in global supply chains. Specifically, it distinguishes between (i) GenAI-enabled sustainability reporting (i.e., automated generation of auditable narrative disclosures from multi-tier supply chain data) and (ii) predictive sustainability analytics (i.e., forecasting tools that anticipate environmental and social risks and support proactive interventions). We propose that both capabilities positively influence sustainable supply chain practices and that these effects are contingent on key boundary conditions: supplier collaboration and regulatory pressure. Drawing on stakeholder theory, the resource-based view and sociotechnical systems theory, the paper develops a conceptual model and associated hypotheses and outlines a quantitative research design using survey data from supply chain and sustainability professionals. The proposed model has been analysed using partial least squares structural equation modelling (PLS-SEM), including interaction (moderation) effects. The study contributes by clarifying the distinct transparency and proactivity pathways through which GenAI can enable accountable, data-driven and sustainable supply chain management. The findings show that predictive sustainability analytics is the most significant predictor of the sustainable supply chain practices, followed by GenAI-enabled sustainability reporting, while regulatory pressure and supplier collaboration play significant moderating roles and their combined effect is also significant. Enriched with the theoretical framework, the study offers meaningful implications for supply chain practitioners, policymakers and decision-makers.

Currently, organizations are facing unprecedented stakeholder expectations for corporate social responsibility (CSR). To face this challenge, responsible leadership is crucial. However, the mechanisms that explain how these leaders encourage CSR engagement are underexplored, emerging as a critical research priority. Drawing on the Social Identity Theory, this study aims to contribute to this purpose by analyzing the influence of responsible leadership on CSR practices evaluated by the employees. Moreover, the mediating role of affective organizational commitment and organizational identification is analyzed in this proposed relationship. Through a cross-sectional design and a purposive sampling technique, 818 employees from different sectors in Bogotá, Colombia, answered the online questionnaires during several training programs. PLS–SEM was performed to test the hypotheses. The findings suggest that responsible leadership plays a crucial role in strengthening CSR practices by fostering organizational identification and enhancing employees' affective organizational commitment. Developing models that explain how leaders foster the CSR practices not only contributes to expanding the existing literature but also can be useful to leaders' recruitment and development, enhancing an organizational CSR engagement aligned with current SDG priorities.

This paper systematically reviews eco-innovation practices in small and medium-sized enterprises (SMEs) to identify their key challenges, enablers, and outcomes. Using the Scopus database, 207 peer-reviewed journal articles published between 2002 and 2025 were analyzed following PRISMA guidelines; the review synthesizes recent evidence on how SMEs adopt and benefit from eco-innovation under increasing sustainability and digitalization pressures. The results indicate that eco-innovation enhances environmental and economic performance when supported by complementary firm-level capabilities, including green intellectual capital, dynamic capabilities, and digital readiness. However, adoption remains uneven due to persistent barriers including financial constraints, managerial inexperience, and weak institutional support. The review also highlights the mediating roles of leadership, human resource management, and collaboration in translating sustainability intent into measurable performance. Theoretically, it advances a capability-contingent and multi-level understanding of eco-innovation, emphasizing the importance of mechanism-based theorizing. Empirically, it suggests that SMEs should integrate technological, human, and organizational initiatives while policymakers develop blended financing and capability-building programs to foster adoption. Overall, this study contributes an updated synthesis that bridges fragmented findings, refines theoretical perspectives, and provides a strategic framework for advancing sustainable innovation among SMEs.