Search Results (57)

This study examines the first corporate disclosures issued under the IFRS Sustainability Standards, with full alignment to IFRS S2, using natural language processing and text mining techniques, and contributes evidence to an underexplored phase of sustainability reporting research. Focusing on an emerging market setting, the analysis covers the 2024 reports of 18 firms included in the Borsa Istanbul Sustainability 25 Index. The reports are evaluated through readability metrics (Flesch–Kincaid, Gunning Fog, and SMOG), conceptual concentration measures (TF–IDF), semantic proximity analysis (Cosine Similarity), and network-based methods. The findings indicate a strong degree of technical discipline and standard adherence in the first year of implementation, alongside a pronounced barrier to linguistic accessibility. Average Gunning Fog and Flesch–Kincaid scores of 18.94 and 14.90 suggest that meaningful interpretation of these disclosures requires advanced academic proficiency. The observed technical density reflects the detailed and standard-driven structure of IFRS-based sustainability reporting and points to a persistent tension between technical precision and interpretability, consistent with the Managerial Obfuscation perspective (H1). High levels of semantic overlap further indicate that, under conditions of reporting uncertainty, firms rely heavily on established disclosure patterns, reinforcing professional convergence through both coercive (regulatory alignment) and mimetic (uncertainty-driven emulation) isomorphism (H2). In contrast, distinct narrative configurations identified through principal component and network analyses are evaluated as potential credibility-enhancing signals within the framework of Signaling Theory (H3). Overall, IFRS Sustainability Standards reporting functions in emerging markets as a learning-oriented and strategically relevant disclosure mechanism that may potentially mitigate information asymmetry through its linguistic properties. Full article

The topic of sustainability reporting by SMEs is gaining significant importance in European contexts such as Italy. However, recent regulations, constantly evolving in terms of legal requirements and practical standards, do not yet provide solid foundations to guide small and medium-sized enterprises. This study aims to examine how Italian listed SMEs address sustainability issues in terms of Sustainable Development Goals (SDGs) in their sustainability reports, in light of the recent requirements set out in European directives (i.e., Directive 2022/2464/EU—Corporate Sustainability Reporting Directive (CSRD) and Directive 2025/794/EU—Stop the Clock). The analysis is based on a content review of 17 sustainability reports published in 2023 by Italian SMEs listed on Euronext Growth Milan of Borsa Italiana. The research protocol was structured around the key SDG themes found in the reports, using Python 3.14.2 libraries including Pandas, NumPy, NLTK, and Matplotlib. The findings highlight heterogeneous approaches to sustainability. Most firms adopt symbolic approaches based on formal narrative disclosures without addressing sustainability reporting’s substantive dimensions. They overlook both the principle of double materiality, actually recommended by the CSR Directive, and the provision of assurance statements on reports. Although mandatory sustainability reporting is not imminent, particularly in light of the “Stop the Clock” measure, this research offers significant insights into both theoretical and practical implications. From a theoretical standpoint, it contributes to the growing body of literature on sustainability practices among SMEs. From a managerial standpoint, it underscores the importance of designing tailored reporting practices for SMEs that avoid administrative costs and overload issues, at the same time fostering a substantive approach to disclosure able to convey meaningful information to stakeholders. Full article

There is substantial empirical heterogeneity in the literature on the intersection between ESG performance and financial outcomes. To address this fragmentation, we foreground ESG integrity, the alignment between sustainability claims and high-quality financial reporting, as the mechanism through which ESG is translated into value. Using Scopus and Web of Science, the study identifies and screens 205 peer-reviewed articles published until October 2025 that jointly address ESG, earnings management, and financial performance. Using VOSviewer and Bibliometrix, we map the conceptual and intellectual structure and synthesize the evidence via interdisciplinary integration. We identify four primary intellectual pillars that govern the ESG–financial performance relationship: national institutions, governance architectures, disclosure quality, and earnings quality. The results suggest a “conditional chain” where ESG tends to be associated with sustained financial value when anchored in rigorous internal governance and high-quality reporting. Conversely, in weak institutional settings, ESG often serves as a “masking” mechanism for managerial opportunism and earnings management. The study reveals a significant shift in the literature from broad corporate social responsibility narratives toward material ESG metrics, gender diversity, and the “Twin Transition” (green and digital). This paper moves beyond traditional descriptive reviews by introducing a conceptual framework to mitigate “construct conflation” between governance and ESG. It provides a critical roadmap for future research, emphasizing the need for causal identification and granular measurement of real versus accrual-based earnings management. Full article

This study examines how sustainability is discursively constructed, prioritized, and selectively institutionalized in the Turkish textile and apparel sector, conceptualizing sustainability reporting not only as an operational practice but also as a form of strategic communication. Drawing on the Triple Bottom Line framework, stakeholder theory, and institutional theory, it employs a theory-informed thematic content analysis of publicly available sustainability-related disclosures from 52 firms operating between 2020 and 2024. Rather than treating these documents as direct representations of organizational practices, the study approaches them as institutionalized communicative artifacts through which firms signal legitimacy, position themselves in relation to key external audiences, and justify particular sustainability orientations. The findings indicate a pronounced institutionalization of environmental narratives, while social and economic dimensions remain comparatively weakly embedded, particularly among small and domestically oriented firms. This imbalance appears to be structurally reproduced through reporting standards, market pressures, and certification regimes that selectively reward environmental compliance. The analysis further suggests that firms cluster into distinct sustainability profiles, reflecting differentiated pathways of institutional alignment rather than a uniform transition process. Theoretically, the study help explains why certain sustainability dimensions become prioritized over others. Empirically, it provides a comparative mapping of firm-level sustainability orientations in an emerging economy context. By conceptualizing sustainability as a signaling and positioning mechanism, the study contributes to marketing and sustainability literature by highlighting how corporate disclosures function as tools of legitimacy construction rather than neutral representations of practice. Full article

The rapid expansion of corporate sustainability reporting has increased transparency requirements while raising concerns about greenwashing driven by selective, narrative-based disclosure. This study assesses the credibility of Environmental, Social, and Governance (ESG) communication by comparing corporate sustainability reports with external media coverage for a sample of 204 large firms operating in Central and Eastern Europe in 2023. Using natural language processing techniques, the analysis constructs a Greenwashing Severity Index (GSI) that captures discrepancies between firms’ ESG self-representation and external public narratives. The index combines ESG-specific focus measures, sentiment analysis, TF–IDF-based term weighting, and topic modeling to quantify imbalances in ESG communication. Results indicate moderate but widespread greenwashing across countries, industries, and firm sizes, with substantial heterogeneity linked to differences in regulatory maturity and stakeholder scrutiny. Higher alignment between corporate disclosures and external narratives is observed among larger firms and in sectors subject to stronger public accountability, while finance, aviation, and online commerce exhibit higher greenwashing severity. A propensity score matching analysis further shows that firms with imbalanced emphasis across ESG dimensions display significantly higher GSI values, consistent with strategic disclosure behavior rather than substantive sustainability engagement. Overall, the findings demonstrate that transparency alone is insufficient to ensure credible ESG communication, highlighting the need for EU sustainability governance to move beyond disclosure-based compliance toward digitalized, data-driven monitoring frameworks that systematically integrate external information sources to curb strategic ESG misrepresentation and enhance corporate accountability under evolving regulatory regimes. Full article

This study proposes a hybrid machine learning framework that integrates structured financial indicators and unstructured textual strategy disclosures to improve firm-level management performance prediction. Using corporate business reports from South Korean listed firms, strategic text was extracted and categorized under the Balanced Scorecard (BSC) framework into financial, customer, internal process, and learning and growth dimensions. Various machine learning and deep learning models—including k-nearest neighbors (KNNs), support vector machine (SVM), light gradient boosting machine (LightGBM), convolutional neural network (CNN), long short-term memory (LSTM), autoencoder, and transformer—were evaluated, with results showing that the inclusion of strategic textual data significantly enhanced prediction accuracy, precision, recall, area under the curve (AUC), and F1-score. Among individual models, the transformer architecture demonstrated superior performance in extracting context-rich semantic features. A soft-voting ensemble model combining autoencoder, LSTM, and transformer achieved the best overall performance, leading in accuracy and AUC, while the best single deep learning model (transformer) obtained a marginally higher F1 score, confirming the value of hybrid learning. Furthermore, analysis revealed that customer-oriented strategy disclosures were the most predictive among BSC dimensions. These findings highlight the value of integrating financial and narrative data using advanced NLP and artificial intelligence (AI) techniques to develop interpretable and robust corporate performance forecasting models. In addition, we operationalize information security narratives using a reproducible cybersecurity lexicon and derive security disclosure intensity and weight share features that are jointly evaluated with BSC-based strategic vectors. Full article

As corporate sustainability reporting evolves into a pivotal resource for investors, regulators, and stakeholders, the imperative to evaluate and elevate ESG disclosure quality intensifies amid persistent challenges like opacity, inconsistency, and greenwashing. This review synthesizes interdisciplinary insights from accounting, finance, and computational linguistics on artificial intelligence (AI), particularly natural language processing (NLP) and machine learning (ML), as a transformative force in this domain. We delineate ESG disclosure quality across four operational dimensions: readability, comparability, informativeness, and credibility. By integrating cutting-edge methodological innovations (e.g., transformer-based models for semantic analysis), empirical linkages between AI-extracted signals and market/governance outcomes, and normative discussions on AI’s auditing potential, we demonstrate AI’s efficacy in scaling measurement, harmonizing heterogeneous narratives, and prototyping greenwashing detection. Nonetheless, causal evidence linking managerial AI adoption to stakeholder-perceived enhancements remains limited, compounded by biases in multilingual applications and interpretability deficits. We propose a forward-looking agenda, prioritizing cross-lingual benchmarking, curated greenwashing datasets, AI-assurance pilots, and interpretability standards, to harness AI for substantive, equitable improvements in ESG reporting and accountability. Full article

This paper develops a quantitative framework for climate–financial risk measurement that combines a spatially explicit jump–diffusion asset–loss model with prudentially aligned risk metrics. The approach connects regional physical hazards and transition variables derived from climate-consistent pathways to asset returns and credit parameters through the use of climate-adjusted volatilities and jump intensities. Fat tails and geographic heterogeneity are captured by it, which conventional diffusion-based or purely narrative stress tests fail to reflect. The framework delivers portfolio-level Spatial Climate Value-at-Risk (SCVaR) and Expected Shortfall (ES) across scenario–horizon matrices and incorporates an explicit robustness layer (block bootstrap confidence intervals, unconditional/conditional coverage backtests, and structural-stability tests). All ES measures are understood as Conditional Expected Shortfall (CES), i.e., tail expectations evaluated conditional on climate stress scenarios. Applications to bank loan books, pension portfolios, and sovereign exposures show how climate shocks reprice assets, alter default and recovery dynamics, and amplify tail losses in a region- and sector-dependent manner. The resulting, statistically validated outputs are designed to be decision-useful for Internal Capital Adequacy Assessment Process (ICAAP) and Pillar 2: climate-adjusted capital buffers, scenario-based stress calibration, and disclosure bridges that complement alignment metrics such as the Green Asset Ratio (GAR). Overall, the framework operationalises a move from exposure tallies to forward-looking, risk-sensitive, and auditable measures suitable for supervisory dialogue and internal risk appetite. Full article

This essay explores how sanctity at Helfta was defined not by the perfection of song but by its interruption. The Book of Special Grace and the Herald of Divine Love praise Mechthild of Hackeborn and Gertrude the Great as singers of surpassing sweetness yet linger on the migraines, collapses, and illnesses that silenced their voices in the choir. These moments of suspension disclose muteness as more than absence: they reveal it as the paradoxical condition through which divine presence most fully resounds. Bringing sound studies into dialogue with disability studies, I argue that faltering breath, broken chant, and enforced silence function as theological and literary form. At Helfta, impairment itself becomes a hermeneutic structure, the hinge through which sanctity is revealed and narrative meaning is generated. In this framework, muteness operates as a form of narrative prosthesis—an interruption that both structures the hagiographical imagination and unsettles it by refusing cure or closure. By highlighting the fragility of voice as the very medium of divine disclosure, these texts testify that the sweetest music of Helfta lies not in unbroken chant but in silence transfigured into revelation. Full article

This study examines how major global hotel groups construct sustainability through corporate communication, assessing both the thematic content and the internal coherence of their Environmental-Social-Governance (ESG) narratives. The research question is How do international hotel corporations construct sustainability through their corporate communication and ESG reporting? The research applies qualitative content analysis of sustainability reports from ten international hotel corporations and a four-layer discursive coherence model (performance, operational, narrative, strategic), the study analyses 888 coded quotations and 205 sustainability-theme occurrences in ATLAS.ti version 25, a qualitative data-analysis software. Results show that while measurable, performance-based disclosures dominate—such as digital food-waste monitoring, emissions-intensity reductions, and responsible sourcing—symbolic language remains strategically deployed to reinforce identity, purpose, and legitimacy. Across the sector, sustainability discourse converges around four recurring pillars: environmental performance leadership, community resilience, responsible business governance, and inclusive economic empowerment. The study advances theoretical work on sustainability communication by conceptualizing discursive coherence as an indicator of organizational authenticity and offers actionable insights for enhancing credibility and stakeholder trust in corporate ESG reporting. Full article

This research evaluates the extent to which firms’ “green” bond disclosures create and convey a meaningful representation of their Environmental, Social, and Governance (“ESG”) commitments. Additionally, this research explores how investors distinguish between disclosures that represent genuine commitment to sustainability and those that may be indicative of “greenwashing,” and how such distinctions impact their assessment of an issuer’s credibility as well as the issuer’s performance subsequent to the issuance of a “green” bond. The methodology employed in this research employs a convergent mixed-methods approach that combines quantitative methods (Natural Language Processing (“NLP”), financial modeling, etc.) with qualitative methodologies (case studies, interviews). The NLP methodology employed in this research includes sentiment analysis, topic modeling, and ambiguity measurement in order to determine the tone, thematic content, and linguistic clarity of the disclosure texts. Subsequently, the results of the NLP methodologies are correlated with firm level outcomes using cross validated partial least squares regression (“PLS-R”), event study methodologies, and one way ANOVA to test for temporal and industrial variability. Finally, the results of the computational and financial methodologies are supplemented by qualitative case studies and interviews to provide context for the patterns identified in the computational and financial methodologies. In summary, the results of this research demonstrate that firms that communicate in a clear, balanced, and verifiable manner experience better market reaction and more favorable accounting results subsequent to the issuance of a “green” bond than do firms whose communications are vague, overly optimistic, or lacking in consistency. Conversely, the findings suggest that investors have become increasingly sensitive to potential “greenwashing” and therefore are less likely to respond favorably to communications characterized by the aforementioned characteristics. Full article

This paper presents a systematic literature review (SLR) of research on strategic positioning of companies and the measurement of greenwashing in sustainability reporting. Its main aim is to synthesize and organize the existing literature, identify key research gaps, and outline directions for future studies. Drawing on a rigorous content analysis of 88 studies, we delineate strategic typologies of greenwashing in sustainability reporting and examine content-analysis-based measurement approaches used to detect it. Our SLR shows that most strategic typologies draw on theories such as legitimacy theory, impression management theory, signaling theory, and stakeholder theory. Several studies adopt a four-quadrant matrix with varying conceptual dimensions, while others classify strategic responses to institutional pressures along a passive–active continuum. However, the evidence suggests that to assume that companies uniformly pursue sustainability reporting strategies is a major oversimplification. The findings also indicate that the literature proposes a variety of innovative, content-analysis-based approaches aimed at capturing divergences between communicative claims and organizational realities—most notably, discrepancies between disclosure and measurable performance, and between symbolic and substantive sustainability actions, as well as the identification of selective or manipulative communication practices that may signal greenwashing. Analytical techniques commonly focus on linguistic and visual cues in sustainability reports, including tone (sentiment and narrative framing), readability (both traditional readability indices and machine learning–based textual complexity measures), and visual content (selective emphasis, imagery framing, and graphic distortions). We also synthesize studies that document empirically verified instances of greenwashing and contrast them with research that, in our view, relies on overly simplified or untested assumptions. Based on this SLR, we identify central theoretical and methodological priorities for advancing the study of greenwashing in sustainability reporting and propose a research agenda to guide future research. Full article

This research conducts a comparative analysis of the Environmental Impact Assessment’s (EIA’s) legal frameworks in Laos and China, utilising a qualitative methodological approach rooted in comparative law. This research systematically examines primary legal documents, case studies from the hydropower and mining sectors, and recent government data to evaluate the two systems based on three core criteria: the robustness of the legal structure, the effectiveness of enforcement mechanisms, and the depth of public participation. The analysis indicates that although both countries require Environmental Impact Assessments (EIAs), China’s framework is more structured and efficient, as demonstrated by its clearer legal hierarchy, strict penalties for non-compliance, and established public disclosure procedures. In contrast, Laos’s framework, although established, is marked by its early stage of development, evident in fragmented legislation, limited enforcement due to capacity constraints, and reduced public engagement. The study contributes by providing a direct bilateral comparison and empirically demonstrating how institutional divergences account for disparities in environmental outcomes and foreign investment. Recommendations are provided to improve transparency, enforcement capabilities, and substantive public engagement in both nations. This research is based on comparative legal theory and institutional analysis to transcend a mere descriptive narrative. It utilises a qualitative comparative methodology that combines doctrinal research of legal texts with practical case studies from the hydropower and mining industries. This method enables us to systematically investigate how differing institutional capacity, enforcement mechanisms, and governance models between an emerging and a developed system account for variations in EIA outcomes. The study questions are formulated to evaluate theoretical claims regarding the influence of legal frameworks and administrative authority on the attainment of good environmental governance, providing a transferable analytical model for analogous developing environments. Full article

Posttraumatic growth (PTG) offers an alternative understanding of trauma response, contrasting with traditional perspectives focused solely on symptom development and resilience. In the PTG model, individuals and groups report positive changes in life philosophy, self-understanding, and interpersonal relationships because of successfully navigating the struggles involved with experiencing adversity. This narrative review includes the evolution of PTG theory, highlighting the disruption of core beliefs, the role of rumination, and the reconstruction of a life narrative as central mechanisms of the PTG process. The authors describe the five empirically validated domains of PTG and outline the naturally occurring PTG process. Methods are discussed for facilitating PTG through “expert companions,” who may be peers or professionals providing nonjudgmental, supportive relationships that encourage emotional regulation, constructive disclosure, and meaning making. The article explores how these methods can be applied to individuals, communities, and organizations, all of which may experience comparable domains of growth following collective adversity. The article concludes by highlighting how a focus on posttraumatic growth shifts perspectives from viewing trauma survivors as broken to recognizing their potential for transformation and underscores the role of both professional and community support in fostering PTG and healthier organizational climates. Full article

Discontinuing active oncological treatment and initiating palliative care is a critical moment in cancer care, requiring oncologists to address complex clinical, ethical, and emotional challenges. This narrative review aims to provide clinicians with practical guidance for conducting conversations about treatment discontinuation and transitioning patients to palliative or hospice care. Drawing from current clinical guidelines, empirical research, and expert perspectives, the article reviews evidence-based communication strategies and frameworks, including the SPIKES protocol, Ask–Tell–Ask, the WHO model, and the disclosure model. The article also explores the clinical, functional, psychosocial, and ethical criteria relevant to treatment withdrawal decisions, as well as the timing and structure of end-of-life discussions. A practical algorithm is proposed, synthesizing key principles into a step-by-step guide for use in daily oncology practice. The algorithm supports clinicians in balancing medical indications with patient values and preferences, fostering shared decision-making and maintaining therapeutic relationships even in the most difficult circumstances. The review concludes that structured yet flexible communication enhances patient understanding, reduces unnecessary interventions, and improves the quality of end-of-life care. By promoting patient-centered care and timely palliative integration, this article offers oncologists a clear and adaptable approach to one of the most sensitive aspects of cancer care. Full article