Search Results (281)

This study compares environmental goal-setting and monitoring priorities of EMAS-registered and non-EMAS organizations in the European Union. Using a dataset of 847 organizations and exploratory factor analysis, it examines differences in the structure of environmental objectives and indicators. The results show that EMAS-registered organizations prioritize operational performance and continuous improvement, while non-EMAS organizations focus more on regulatory compliance, awareness-building, and external communication. EMAS participation is associated with a more integrated and strategic approach to environmental management, linking objectives with measurable performance indicators. In contrast, non-EMAS organizations often adopt more symbolic or externally oriented practices driven by legal and reputational concerns. To isolate the effects of formal verification and transparency, ISO 14001 certification is not treated separately; instead, EMAS organizations are compared with all non-EMAS entities. The findings provide new empirical evidence on how voluntary environmental schemes shape organizational behavior by improving alignment between goals and indicators. They also offer practical guidance for organizations preparing for the EU Corporate Sustainability Reporting Directive (CSRD) and European Sustainability Reporting Standards (ESRS), highlighting EMAS as a model for credible, performance-based environmental reporting. Full article

The energy transition constitutes not only a technological and regulatory challenge but also a communicative and cultural one, in which corporate narratives play a decisive role in shaping social understanding, legitimacy, and trust. This study examines how major energy companies operating in Spain construct the narrative of the energy transition through their corporate discourse and evaluates the extent to which these narratives integrate pedagogical and relational dimensions oriented toward society. Using a qualitative content analysis approach supported by lexical frequency analysis as a heuristic tool, the study analyzes the CEO or Chair letters published in sustainability reports by four energy companies—Iberdrola, Endesa, Naturgy, and Holaluz—over a five-year period (2020–2024), comprising a total of 20 reports, from which 18 CEO/Chair letters were extracted and treated as a single analytical unit. Two reports (Iberdrola and Naturgy, 2024) adopted the ESRS/CSRD format directly, eliminating the traditional chairperson’s letter. To triangulate and contextualize the documentary analysis, a two-round Delphi study was conducted with 11 independent experts. The findings reveal a predominantly technical and self-referential discourse focused on corporate strategy, performance, and regulatory compliance, with a limited presence of explanatory or citizen-oriented narratives. Despite increasing terminological convergence driven by regulatory standardization, the analysis reveals persistent divergence in narrative framing, with the challenger company articulating purpose-driven and citizen-empowerment frames largely absent from incumbent discourse. The Delphi results reinforce these findings, emphasizing the need to strengthen pedagogical clarity, accessibility, and relational orientation in energy communication. On this basis, the study proposes a relational model of energy communication that highlights narrative mediation, social intelligibility, and stakeholder-oriented discourse as key factors for enhancing legitimacy and trust in the context of the energy transition. The analysis further identifies a structural tension between regulatory standardization and narrative capacity, exemplified by the elimination of the CEO letter in one company’s 2024 report following ESRS adoption. Full article

Tax systems worldwide face a compliance gap that OECD data places at USD 100–240 billion annually in corporate avoidance alone, before accounting for the shadow economy and crypto-asset transactions. FinTech mandatory e-invoicing, real-time transaction matching, and machine-learning audit selection is narrowing the informational conditions that enable evasion, while simultaneously introducing governance risks: opaque algorithmic audit targeting, contested blockchain forensic evidence, and the surveillance potential of programmable money. This article presents a PRISMA 2020 systematic literature review of 59 peer-reviewed articles (Scopus, Web of Science, and ScienceDirect), complemented by IRAMUTEQ lexicometric analysis and an extension of the Allingham Sandmo compliance model to incorporate algorithmic detection probabilities, bomb-crater belief dynamics, and Zero-Knowledge Proof verification. Four thematic clusters emerge: tax compliance behaviour and FinTech adoption (19.92%), digital transformation and corporate performance (35.34%), bibliometric and emerging-technology research (16.54%), and cryptocurrency markets and regulatory challenges (28.20%). Across them, FinTech reduces evasion where institutional and technical conditions allow but generates distributional, evidentiary, and constitutional risks that existing legal frameworks have yet to resolve. In response, we propose the Techno-Legal Due Process Framework (TLDPF) three pillars (Techno-Proportionality, Cryptographic Burden of Proof, and Algorithmic Constitutionalism) grounded in EU/OECD constitutional doctrine as a normative design proposal awaiting empirical validation. Full article

Digital Transformation (DT) increasingly relies on project-based organizing to develop and deploy new capabilities, yet corporate innovation projects frequently stall not for lack of ideas but because of recurring governance and resource-commitment bottlenecks. This study presents a micro-longitudinal, AI-enabled, and human-reviewed analysis of 711 episodes drawn from 28 weekly project governance meetings across two corporate startup initiatives participating in the same internal incubation program, conducted between November 2024 and April 2025. Employing a six-stage analytical pipeline that combines episode-level segmentation, linguistic tension markers, and a large language model (LLM) classifier, we identify 28 decision-relevant governance tensions, which are then abductively grouped into 13 project governance dilemmas and mapped onto Teece’s dynamic capabilities framework (sensing, seizing, reconfiguring). The key finding is that 62% of dilemmas are structural in nature—reflecting persistent governance design tensions between autonomy and control, compliance and agility, and centralization and decentralization—and that 69% concentrate at the seizing stage, corresponding to resource-commitment and execution decisions. This pattern indicates a governance choke point in corporate DT projects that is structural and decisional rather than ideational. By shifting attention from lagging indicators (overruns) to governance tension leading indicators, the approach supports earlier interventions to reduce decision latency and protect project delivery performance. We further synthesize two incubation-specific meso-level governance dilemmas—stakeholder engagement and compliance vs. agility—that serve as transmission mechanisms between macro structural constraints and micro-level decision bottlenecks. The AI-enabled pipeline is proposed as a replicable early-warning system for project governance tensions in organizations pursuing digital transformation. Full article

Against the backdrop of increasingly stringent environmental regulation and increasing uncertainty in supply chain operations, this study examines how environmental penalties affect corporate supply chain resilience. Using Chinese A-share listed firms from 2009 to 2024, this paper constructs a firm-level panel dataset and employs a two-way fixed-effects model to estimate the relationship between environmental penalty intensity and supply chain resilience. Environmental penalty intensity is measured by the annual penalty amount imposed on each firm, while supply chain resilience is captured through an entropy-weighted index reflecting both resistance and recovery capacities. To alleviate endogeneity concerns, this study further uses an instrumental-variable approach based on the interaction between a firm’s one-year lagged penalty amount and city-level thermal inversion days. The results show that environmental penalties reduce corporate supply chain resilience. This negative effect is heterogeneous across firm characteristics and is partially mediated by reduced operational efficiency and crowded-out R&D investment. This conclusion remains robust after replacing the dependent variable, changing the clustering level of standard errors, and excluding observations from the COVID-19 pandemic period. Mechanism tests suggest that environmental penalties weaken supply chain resilience partly by reducing operational efficiency and crowding out R&D investment. Heterogeneity analysis indicates that the negative effect is more pronounced among young firms, non-high-tech firms, and firms located in regions with lower environmental regulation intensity. This study contributes to the literature by distinguishing environmental penalties from broader environmental regulation and by examining their implications for supply chain resilience. The findings also suggest that environmental enforcement should maintain deterrence while improving transparency, predictability, and targeted compliance guidance. Full article

Saudi Arabia’s audit market faces three governance challenges that existing frameworks may not fully address. These challenges concern a potential regulatory gap around autonomous AI accountability, a trust dimension that standard technology-adoption models may not fully capture, and limited mechanisms for independently verified ESG assurance under Vision 2030. This study adopts a conceptual design approach within the design science research tradition and proposes the CMA Agentic AI Platform as a practical response to these challenges. The platform comprises two segments. Segment 1 deploys autonomous drone swarms to verify corporate assets across four audit tasks—asset valuation, ESG compliance, anomaly detection and construction progress—using deep learning, thermal imaging and social-media cross-referencing. Segment 2 continuously monitors discretionary accruals and uses objective earnings-management data to inform auditor assignment and rotation decisions. This approach replaces subjective reputational assessments with transparent, quantifiable governance criteria. The platform is governed through the Triadic Agentic Framework, which extends classical agency theory by distributing authority across the Principal, the Human Agent and the AI Agent. The framework also operationalises Trust Expectancy as the primary adoption condition. The evidence base draws on two complementary streams: a PRISMA-guided systematic review and bibliometric analysis of thirty-nine peer-reviewed studies, and a documentary analysis of four national agentic-AI regulatory frameworks (SDAIA, MDDI/IMDA, NIST and ICO). The study contributes the concept of Algorithmic Accountability as a distinct governance domain, the Triadic Agentic Framework as an operational architecture for autonomous regulatory monitoring, and a reframing of the UTAUT trust construct for agentic-AI adoption in mature professional contexts. The platform converts theoretical governance into a regulatory architecture with direct implications for concentrated capital market regulators. Full article

Corporate balance sheets report aggregate equity and liability totals but conceal the internal allocation of financing sources across asset categories—an identification problem that conventional econometric methods cannot resolve without additional parametric assumptions. This paper develops a maximum entropy (ME) panel estimator to recover two latent scalar parameters: x ∈ (0,1), the share of equity capital directed toward long-term asset financing, and y ∈ (0,1), the corresponding debt allocation share. Grounded in maximum entropy principle, the estimator selects the unique parameter vector that satisfies the mean-level balance-sheet constraint while maximising joint Shannon entropy—the least-biassed solution consistent with observable data. The closed-form logistic representation yields a scalar Lagrange multiplier λ*, interpreted as a financing pressure index, recoverable via bisection in at most 21 iterations at tolerance ε = 10⁻⁵. Building on the ME estimates, we introduce a continuous matching alignment index M* = x* − y* that measures the degree of compliance with the financial matching principle along a continuous spectrum rather than as a binary categorisation. Applied to a ten-firm, cross-sectoral panel spanning Technology, Finance, Energy, and Automotive sectors over an observation window spanning 2001 to 2025 (with firm-specific subperiods reflecting differences in IPO dates and data availability), the framework reveals substantial heterogeneity in latent financing flows: equity allocation shares range from 30.1% (NVIDIA) to 75.1% (ExxonMobil), while debt allocation shares span 37.1% to 77.5%. Across the panel, only Meta exhibits substantial positive matching alignment, while Microsoft, ExxonMobil, Apple, and Tesla show only very slight differences that fall within the neutral band, and the remaining firms show varying degrees of structural departure from the matching benchmark; the thresholds used to summarise these descriptive labels are interpretive aids rather than re-imposed binary criteria, and the substantive ranking of firms along M* does not depend on the specific threshold values adopted. The ME solution’s entropy H(x*, y*) and the normalised diversification index D(x*, y*) describe allocation balance under the estimator’s information–theoretic criterion rather than independently observed firm complexity; in the present sample, the cross-firm ordering of these values is not recovered by firm size, leverage, or sector classification alone. These findings, based on a ten-firm case-study panel with time-invariant allocation parameters, should be interpreted as descriptive patterns of the present sample rather than statistically validated regularities. They provide a theoretically rigorous and computationally tractable identification of unobservable corporate financing flows, with potential implications for capital structure theory, financial risk assessment, and balance sheet analysis that would benefit from validation on larger and more representative samples in future work. Full article

Using data from the 41 companies listed on the Borsa Istanbul Sustainability Index between 2020 and 2024, this study examines the relationship between board characteristics, concentrated ownership structure, shareholder activism and sustainability transparency. Reports published on a voluntary basis were subjected to content analysis based on criteria selected from the Global Reporting Initiative (GRI) standards, and a sustainability disclosure score was calculated. The relationship between board characteristics, concentrated ownership structure, shareholder activism, financial metrics identified as control variables, and sustainability scores was evaluated via robust random effects (static) and System Generalized Method of Moments (System GMM) (dynamic) panel data estimators. According to the static estimation results, board meeting frequency and the ratio of female members serve as positive drivers for sustainability transparency. In the dynamic model estimates, these governance mechanisms lose their explanatory power and show no statistically observable effect. However, across both methodological approaches, firm size, which was integrated as a control factor, consistently demonstrates a robust positive correlation with levels of disclosure. These findings reveal that governance mechanisms such as the percentage of female members and meeting frequency have a short-term and marginal effect, but structural factors such as company size are the main determinants for a long-term and sustainable level of transparency in Türkiye. Consequently, market regulators should deploy policy frameworks that incentivize disclosure trajectories aligned with international frameworks while fostering voluntary reporting. Concurrently, corporate managers should look beyond mere statutory compliance and continuously embrace extensive global reporting standards. Full article

The global regulatory landscape is shifting from voluntary corporate social responsibility (CSR) reporting to mandatory Environmental, Social, and Governance (ESG) disclosure, yet whether this transition drives substantive corporate environmental change or merely symbolic compliance remains empirically contested. This study investigates the causal impact of mandatory ESG disclosure on firm value and operational carbon intensity, drawing on an unbalanced panel of 9682 firm-year observations for 1626 listed firms from the European Union (EU-27) and Japan covering the period 2018 to 2024. The EU serves as the treatment group, where mandatory disclosure requirements escalated substantially from 2021 onward through the Sustainable Finance Disclosure Regulation and the Corporate Sustainability Reporting Directive proposal. Japan serves as the control group, representing a developed economy with sophisticated capital markets and high ESG awareness that maintained a voluntary disclosure environment throughout the study period. A Difference-in-Differences framework with firm- and year-fixed effects is employed, and causal identification is validated through a dynamic event study analysis. Three principal findings emerge. First, mandatory ESG disclosure is not associated with a statistically significant improvement in firm value in the EU–Japan comparative context, a result that is interpreted as descriptive rather than causal given evidence of pre-existing valuation divergence between the two groups. Second, mandatory disclosure is associated with a significant and progressive reduction in Scope 1 and 2 carbon intensity, indicating substantive operational decarbonization rather than symbolic compliance. Third, this emissions-reducing effect is significantly amplified among firms with dedicated CSR sustainability committees, while the board independence policy indicator yields no significant moderating effect, a finding attributed to data limitations. These results carry direct implications for policymakers designing climate-related disclosure frameworks and for scholars examining the boundary conditions under which mandatory transparency translates into genuine environmental performance. Full article

Environmental governance plays a critical role in shaping the effectiveness of sustainability certification implementation in perennial plantation systems, particularly in oil palm plantation landscapes associated with forest transformation and socio-ecological risks. In Indonesia, the Indonesian Sustainable Palm Oil (ISPO) scheme functions as a mandatory certification system aimed at strengthening environmental accountability. However, variations in implementation outcomes suggest that compliance alone does not guarantee effective certification implementation. This study examines how internal governance mechanisms shape ISPO implementation within a specific plantation organizational context by focusing on the transition from compliance-oriented practices to sustainability-oriented commitment. Using survey data from an ISPO-certified plantation in West Kalimantan and applying partial least squares structural equation modeling (PLS-SEM), the study tests a mediation model linking green training effectiveness, sustainable work environment, and environmental compliance transparency to certification outcomes through corporate environmental commitment. The results show that Corporate Environmental Commitment fully mediates the effects of Green Training Effectiveness and Sustainable Work Environment on ISPO Implementation Success, indicating that organizational conditions contribute to certification effectiveness only when they are translated into governance commitment. In contrast, Environmental Compliance Transparency does not significantly influence commitment formation or certification outcomes. These findings suggest that effective certification implementation depends less on procedural compliance and more on the internalization of environmental priorities into organizational governance routines. The study contributes to the environmental governance literature by demonstrating that sustainability certification effectiveness emerges through governance internalization processes rather than through organizational practices alone. Full article

In green credit markets, information asymmetry and corporate greenwashing increasingly undermine the efficiency of resource allocation, while traditional assessment models relying on static, self-reported environmental data fail to impose effective constraints. To address this limitation, this paper develops a dynamic corporate carbon credit evaluation framework by integrating multiple sources of physical (hard) signals and embeds it into commercial banks’ credit management systems. Anchored in multi-source power-carbon signals (e.g., carbon intensity and compliance records), the framework integrates verifiable physical metrics with ESG disclosures via a Bayesian AHP–CRITIC weighting scheme to construct a dual-dimensional classification scheme (“Credit Rating–Green Label”). It further embeds carbon credit scores into dynamic adjustments to credit limits and differentiated interest rate pricing, forming an integrated risk management mechanism. Empirically, a stratified validation strategy is adopted. Analysis based on a sample of 3327 firms shows that the proposed framework achieves a classification consistency of 81.3%, significantly outperforming both a financial-only baseline model (46.8%) and models based on voluntary carbon disclosure (61.4%). Ablation studies further confirm that physical (hard) signal indicators contribute substantially to ranking stability. Moreover, panel regression analysis, based on 36,185 firm-year observations from 3327 firms over the period 2000–2023, demonstrates that carbon credit scores have robust predictive power for future financial distress. Overall, the proposed framework offers a sustainable, data-driven approach to green credit risk management. Full article

Play is considered the primary activity of children, and toys are their essential tools. However, the toy industry extends beyond children, constituting a significant economic sector with annual revenues exceeding one hundred billion dollars and generating substantial environmental consequences. These include resource consumption, pollution during manufacturing, energy use, consumables during operation, and waste generation at the end of the product’s life cycle. This research presents a study of the state of the art of ecodesign in the toy sector and its potential within this field. Through the analysis of the available scientific literature and the expertise of the Toy Technology Institute (AIJU), experiences from companies in the sector have been identified and classified according to the ecodesign strategy wheel. Simultaneously, a survey of industry stakeholders compared the current situation with that of 30 years ago. The results reveal perceptual progress that is uneven across dimensions, with the strongest advances in materials and production, moderate gains in distribution and end-of-life strategies, and limited improvement in product durability, while innovation in new product concepts shows the highest growth. Correlation analyses indicate that experience and professional background influence how sustainability progress is perceived. Although most improvements have been motivated by cost reduction and regulatory compliance rather than environmental awareness, recent trends reflect a growing corporate commitment to ecological innovation. For consumers, it remains essential to overcome misconceptions about eco-friendly toys, while companies must continue to invest in new materials, technologies, and design strategies that support the transition toward circular and long-lasting toy products. Full article

While theory casts family firms as long-term stewards, rising global demands for sustainability create a practical conflict: unique family goals often clash with formal institutional expectations, leaving the true nature of their corporate social responsibility disputed. This tension motivates this investigation into how family ownership shapes the strategic divergence between substantive and symbolic ESG performance. Analyzing over 4000 public companies across twenty-seven countries, I identify a unique reputational caution model of governance. Empirical results reveal a consistent management lag—family firms systematically underperform in social initiatives and ESG management quality compared to non-family counterparts. Robustness checks using instrumental variable and endogenous treatment models confirm a significant measurement deficit, showing that family firms are less likely to track scope 1 and 3 emissions. These findings reveal a strategic divergence: despite higher emissions under concentrated control, family firms avoid greenwashing and non-compliance. Socioemotional wealth acts as a reputational floor, where the high affective cost of scandal deters active deception. This pattern persists across legal origins and is pronounced in weak macro-governance environments. Ultimately, family-firm ESG behavior is driven by avoidance of negative signaling rather than proactive stewardship. Full article

The retail fuel trade in urban areas presents relevant environmental risks, requiring systematic sustainability assessments. This study aims to highlight the socioenvironmental performance of gas stations in Mossoró, RN, using the Corporate Sustainability Index (ISE). It is a descriptive and exploratory case study based on questionnaires administered to managers of 12 licensed stations. The ISE was calculated from 17 environmental, legal, social, and operational indicators, equally weighted. The results indicated a predominance of high sustainability performance, with 91.7% of the enterprises presenting an ISE above 75%, associated with operational organization, preventive practices, and compliance with legal requirements. However, part of the actions remains tied to regulatory compliance, revealing a predominantly reactive environmental management profile. This study provides support for improving strategic environmental management in the urban context of Brazil’s semi-arid region. Full article

Expanding ESG disclosure mandates under the Corporate Sustainability Reporting Directive (CSRD) and the International Sustainability Standards Board (ISSB) have driven rising demand for artificial intelligence (AI) and data analytics capable of supporting sustainability reporting and verification at scale. Nevertheless, the scholarly literature remains dispersed across discrete disciplinary fields—natural language processing, machine learning, auditing, and regulatory compliance—with limited integrative synthesis. To address this gap, the present study conducts a PRISMA 2020-compliant systematic review of 45 peer-reviewed articles indexed in Scopus and published between 2020 and 2025. The methodology combines bibliometric mapping through VOSviewer with qualitative thematic content analysis. Findings document a rapidly expanding field exhibiting a compound annual growth rate of 91.9%. Four principal thematic dimensions emerge: (i) NLP and text mining for ESG disclosure analysis; (ii) machine learning for ESG scoring and corporate performance; (iii) AI-enabled ESG assurance, auditing, and governance; and (iv) regulatory frameworks and the digital transformation of sustainability reporting. The evidence indicates that AI is progressively reshaping ESG disclosure from a largely narrative and self-reported practice into a data-driven, independently verifiable transparency system. These developments carry substantive implications for regulators, corporate practitioners, assurance providers, and investors seeking to strengthen the reliability and comparability of sustainability disclosures. Full article