Search Results (1,269)

Urban tourism is frequently promoted as a driver of regeneration, competitiveness, and local economic growth. However, its expansion increasingly generates overtourism, environmental degradation, social inequality, gentrification pressures, and cultural commodification in densely populated cities. Although existing tourism research has examined these challenges from managerial, planning, and sustainability perspectives, less attention has been paid to their ethical foundations. This conceptual paper addresses that gap by developing an integrated ethical framework for sustainable urban tourism through a structured, theory-driven synthesis of literature in environmental ethics, social justice theory, virtue ethics, and urban tourism studies. The paper makes three main contributions: it reframes urban tourism growth as a moral and normative issue rather than merely an economic one; it organizes the key ethical dilemmas of urban tourism as interconnected outcomes of growth-oriented development; and it links ethical principles to stakeholder responsibilities and desired governance outcomes. The proposed framework positions tourists, businesses, and policymakers as moral agents and identifies ecological integrity, social equity, and cultural protection as core criteria for evaluating tourism development. As a conceptual study, however, the framework remains theoretical and requires future empirical application and testing across different urban contexts. Full article

This article examines The Mark of Cassandra by Chingiz Aitmatov through the emerging framework of Blue Humanities. While most prior studies have approached Aitmatov’s ecological concerns from a land-based ecocritical perspective, this article shifts the focus to his engagement with oceanic themes and marine environments. By combining literary interpretation with ecological philosophy, the study suggests that The Mark of Cassandra goes beyond the limits of traditional environmental fiction. It presents the ocean not only as a setting but as a source of knowledge and ethical reflection. In this way, Aitmatov’s work seems to anticipate current global discussions on climate change, biodiversity loss, and environmental justice. The novel encourages readers to reconsider the human-centered worldview and adopt a more ecocentric approach. Through its marine symbolism and critical stance on human exploitation of nature, the text offers valuable insights into ecological ethics that cross both national and species boundaries. Overall, this article argues that The Mark of Cassandra is an important literary contribution that challenges the usual borders of ecocriticism and calls for a more integrated and holistic understanding of environmental issues. Full article

Due to acute resource constraints and environmental turbulence, many small and medium-sized construction enterprises (SMEs) prioritize short-term survival over corporate social responsibility (CSR) initiatives. Grounded in social exchange theory (SET), this study investigates how CSR implementation drives financial performance (FP) via the mediating role of non-financial performance (NP), aiming to deconstruct the “psychological black box” of this transformation. Drawing on a sequential mixed-methods design involving PLS-SEM analysis of 380 responses and 10 semi-structured interviews, the results confirm that CSR practices, particularly ethical practices and community engagement, can be effectively translated into improved NP, which acts as a vital strategic conduit for enhancing FP. However, skills development and training showed limited immediate impact due to a systemic “digital mismatch” and significant time-lag effects. Theoretically, this research refines SET by identifying a hierarchical transition where socio-emotional assets serve as compensatory resources in volatile and resource-constrained environments. Practically, the findings offer a strategic roadmap for SMEs to mitigate technological and systemic barriers, providing novel pathways for fostering CSR to achieve sustainable growth. Full article

This study investigates the determinants of borrower repayment intentions in Marketplace Lending (MPL) platforms, focusing on the interplay between behavioural factors and Environmental, Social, and Governance (ESG) awareness in the Hungarian context. A Partial Least Squares Structural Equation Modelling (PLS-SEM) approach was employed to analyze survey responses from 477 participants familiar with MPL platforms. The study integrates constructs from behavioural finance (Perceived Usefulness, Perceived Ease of Borrowing, Theory of Planned Behaviour) and ESG-related factors (Socially Responsible Investment Theory, Reciprocity Theory) to assess their influence on repayment intentions. Perceived Usefulness (PU) emerged as the strongest predictor of Repayment Intention (RI) (β = 0.554, p < 0.001), highlighting the importance of platform functionality. Socially Responsible Investment Theory (SRIT) also had a significant positive impact (β = 0.194, p < 0.01), suggesting that ethical lending practices enhance borrower accountability through reciprocity mechanisms. Conversely, Continuance Intention to Borrow (CIB) and Credit Risk Theory (CRT) showed no significant effects. This study contributes to the literature by bridging behavioural finance, credit risk theory, and ESG principles in FinTech lending, offering a novel framework for sustainable lending practices. Full article

Background/Objectives: Genetic identification of human skeletal remains plays a pivotal role in forensic investigations when other traditional or primary methods are not appropriate. Decomposition, storage and environmental conditions often leave the skeletal structure as the only basis for identification. This review synthesizes current methodologies and technological advances in damaged DNA extraction and analysis, emphasizing the forensic relevance of skeletal remains for genetic identification. Methods: A comprehensive literature analysis highlights the basis of genetic identification; sampling that considers intrinsic and extrinsic factors influencing the DNA yield and its quality; pre-treatment methods; extraction protocols that are suitable for its sensitivity; genetic marker panels that allow for human identification; and statistical evaluation and analysis of the results. The last chapter demonstrates the real-world impact of genetic identification on historical cases, underscoring its broader significance in legal, humanitarian, and socio-historical contexts, supporting a critical evaluation of best practices, methodological robustness, and ethical considerations within the field. Results: Teeth, femur and the petrous portion of temporal bone are the main samples used for genetic analysis. STR profiling and mitochondrial DNA are the gold standard markers for skeletal human identification. Minimally destructive protocols that enhance a high DNA yield are chosen, with silica-based methods being highlighted in the extraction protocols. Next-Generation Sequencing techniques have also improved analytical outcomes, by enabling high-throughput data generation, increased coverage depth, nucleotide-level sequence data, and high-level multiplexing of genetic targets. Conclusions: This review provides a comprehensive framework for researchers and practitioners seeking to optimize genetic identification workflows in forensic sciences and bioarcheology. These methodological advances have significantly increased identification success rates, especially in cases involving degraded or limited skeletal remains. Reviews such as this one help us to identify methodological gaps, ethical concerns, and future research directions, thereby establishing best practices when working with highly degraded skeletal material, supporting more reliable, standardized, and legally defensible applications of genetic identification in forensic, archeological, and humanitarian contexts. Full article

Toxoplasma gondii is an intracellular protozoan transmitted via environmentally resistant oocysts present in food and water, as well as through the consumption of meat containing infective bradyzoites. This study evaluated the inactivation of T. gondii oocysts and bradyzoites (ME-49 strain) by Pulsed Electric Field technology (PEF). Treatment efficacy was determined by mouse bioassay combining brain qPCR and indirect immunofluorescence (IFA), with complementary qPCR in Hs27 cells. The infectious dose (ID₅₀) of T. gondii was estimated at 34.6 oocysts. PEF-treated oocysts (15 kV/cm; 50 kJ/kg; 225 µs) showed a significant reduction in infectivity compared with untreated controls; accordingly, the dose required to establish infection increased to 85.3 oocysts after PEF treatment. Brain qPCR and IFA were highly correlated, whereas heart tissue was less sensitive. Bradyzoites recovered from PEF-treated meat (3.3 kV/cm; 27 kJ/kg; 1600 µs) showed a 50% infectivity reduction compared with untreated samples. In vitro assays confirmed an in vivo reduction in infectivity, indicating that cell cultures can serve as an ethical and efficient tool for preliminary viability assessment. This is the first evidence of T. gondii inactivation by PEF, highlighting its potential as a non-thermal strategy. Further studies are needed to optimize treatment parameters. Full article

Due to the recent rapid development of artificial intelligence (AI) and its expanding impact on the planet, green and sustainable AI research has increasingly gained attention. This systematic literature review searches main databases, including Scopus, Web of Science, and Google Scholar, using an organized methodological approach. Following a thorough screening process, 49 final studies published between 2016 and 2026 are selected from an initial identification of 325 original records. We identify and analyze four key categories of sustainable AI practices: (1) model-level algorithmic efficiency, (2) hardware- and system-level optimization, (3) lifecycle- and data-centric approaches, and (4) operational and policy-level sustainability. We also highlight and explain four dimensions at the intersection of AI and environmentally responsible behavior: AI for sustainable applications’ development in industries, ethical considerations and accountability in using AI, and opportunities enabled by generative AI. We then combine existing taxonomies, evaluation metrics, and challenges to identify areas for improvement and suggest future research directions. Based on our analysis, we emphasize the need for interdisciplinary cooperation to facilitate responsible AI innovation and match it with global sustainable development goals (SDGs). We also highlight the importance of developing adequate frameworks along with precisely defined and standardized metrics to assess the environmental impact of AI. This review aims to encourage more responsible and environmentally friendly AI practices by providing a structured framework for researchers, educators, and professionals engaged in sustainable AI. Full article

Social washing refers to the strategic exaggeration or misrepresentation of an organisation’s commitment to social responsibility, ethical governance, or social impact without corresponding substantive action. It typically operates through selective disclosure, symbolic initiatives, or performative communication that aligns the organisation with socially desirable values—such as equity, human rights, community development, or inclusion—while underlying practices remain unchanged, weakly evidenced, or contradictory. The concept belongs to the wider family of “washing” phenomena associated with corporate social responsibility (CSR) and environmental, social, and governance (ESG) frameworks, especially the difficult-to-measure social (“S”) pillar. By contrast, authentic accountability refers to governance and reporting practices that connect institutional commitments to verifiable social outcomes and discernible improvements in human well-being. The institutionalisation of ESG frameworks has raised expectations of corporate responsibility while also enlarging the scope for reputational manipulation. Within this setting, social washing has become relevant not only to social policy and sustainable development debates, but also to corporate governance, ESG evaluation, and cross-sector partnership practice. This entry examines how organisations construct narratives of social responsibility that do not necessarily correspond to substantive social outcomes. It also argues that such distortions matter both for welfare systems and civil-society actors and for ESG assessment, reputational signalling, and the interpretation of social performance in market settings. Full article

Background/Objectives: Bloodstain pattern analysis (BPA) is widely used in crime scene investigation (CSI), yet its practical application, evidential limits, and interpretive role are often discussed in fragmented or technique-focused terms. This systematic literature review examines how BPA is used in CSI, with emphasis on its operational functions, interpretive scope, and scientific robustness. Methods: The review followed PRISMA 2020 guidelines. A comprehensive search was conducted in Scopus using predefined Boolean strings. After screening, eligibility assessment, and manual review, 18 peer-reviewed research articles published between 1996 and 2026 were included. Data were extracted systematically and analysed using thematic synthesis. Results: The findings show that BPA is applied in CSI as an integrated evidential pathway rather than as a single analytical procedure. Its uses include bloodstain detection and documentation, geometric reconstruction through trajectory and area-of-origin analysis, differentiation of mechanisms and sources to prevent misclassification, activity-level inference based on transfer and contact phenomena, and temporal reasoning related to trace formation. The review also highlights the role of validation infrastructures, including blood substitutes, animal analogues, and computational methods, which support training, experimentation, and reproducibility under ethical and practical constraints. Across the literature, reconstruction accuracy is shown to be sensitive to documentation quality, measurement assumptions, environmental conditions, and contextual limitations. Conclusions: Overall, BPA contributes to CSI by enabling structured, context-aware interpretation of blood evidence while remaining subject to measurement assumptions, contextual influences, and cognitive factors that may affect reconstruction outcomes. Its evidential value lies not only in reconstructing events, but also in supporting transparent, testable, and defensible forensic reasoning. Full article

Uncrewed aerial systems (UASs) have diverse applications in natural environments, yet their deployment can inadvertently disturb wildlife. This PRISMA-guided systematic review synthesised 39 studies (2015–2025) encompassing birds, mammals, and marine taxa to identify UAS operational drivers of disturbance. We applied a Factors–Responses–Consequences (F–R–C) framework linking UAS operational characteristics, observed wildlife responses, and ecological consequences. Three patterns emerged: (i) Factors: Contextual and operational conditions such as flight altitude, noise, and approach direction interact with species-specific sensitivities to shape disturbance potential. (ii) Responses: Physiological measures (e.g., elevated heart rates) often reveal hidden stress not evident from behaviour alone. (iii) Consequences: Short-term effects may accumulate into long-term impacts on health, reproduction, and habitat use. These findings highlight the need for species- and context-specific flight envelopes rather than solely uniform altitude limits. By structuring existing evidence within the F–R–C framework, this synthesis provides a transferable foundation for UAS mission planning, drone development, operational decision-making, ethical practice, and environmental impact assessment in conservation and wildlife-management contexts. As all screening and data extraction were conducted by a single reviewer, the findings should be interpreted with appropriate caution pending independent validation. Full article

This study investigates how environmental consciousness motivations—grounded in Corporate Social Responsibility (CSR) theories (instrumental, political, integrative, and ethical)—influence environmental management performance (MP) and indirectly affect operational performance (OP). Specifically, the research examines these motivations under the intensifying pressure of the Carbon Border Adjustment Mechanism (CBAM) within manufacturing firms in Türkiye. From a cost–benefit perspective, the study addresses whether dominant instrumental (cost-oriented) consciousness acts as a barrier to innovation-led gains predicted by the Porter Hypothesis. Analyzing data from 400 managers using the PLS-SEM method, findings reveal that while ethical and political consciousness positively enhance MP and OP, instrumental consciousness—driven by short-term cost-compliance pressures—exerts a significant negative impact. Furthermore, the statistical insignificance of integrative consciousness highlights a strategic integration gap for manufacturing enterprises in Türkiye. These results demonstrate that perceiving environmental regulations merely as a “cost burden” creates a structural barrier that breaks the strategic productivity cycle. The study concludes that to achieve a positive multiplier effect on competitiveness, firms must transition from instrumental compliance to integrated strategic commitment, guiding managers to distinguish between short-term instrumental efforts and long-term strategic commitments. Full article

This article presents an autoethnographic narrative account of curating and performing two pieces for solo piano and string orchestra—Climate Concerto by Brian Field and Eclogue by Gerald Finzi—to advocate for climate action. It discusses the selection of a concert venue that could be “thickly lived”, offering layers of cultural, historical and aesthetic resonance, and a concert date that could generate “interaction chains”, where engagement in one event motivates engagement in others. The article reflects on the multiple forms of loss brought about by the climate emergency, exploring Field’s musical portrayal of environmental loss and Finzi’s evocation of a harmonious human-nature relationship, which highlights a way of being-in-the-world that has been lost. In response to pervasive pessimism and dystopian narratives in climate communication, the discussion foregrounds hope as a powerful motivator for positive action, showing how the narrative scope of Field’s large-scale forms and the aesthetic beauty of Finzi’s music can elicit felt hope. The article also advocates for gentle musical activism for climate action, emphasising music’s capacity to cultivate relational sensitivity, ethical responsiveness, and collective responsibility toward each other and the world—even amid ecological crisis, social fragmentation, and uncertainty. Full article

Tropical forests, despite their critical environmental and socio-economic roles, remain highly vulnerable to deforestation, forest degradation, and climate-related disturbances. There is a growing demand for robust and transparent forest monitoring systems, particularly under REDD+, the Paris Agreement’s Enhanced Transparency Framework (ETF), and emerging climate-finance mechanisms. Conventional approaches based on field inventories and traditional remote sensing are often constrained by limited or uneven field data, persistent cloud cover, complex forest conditions, and limited institutional and technical capacity. This review examines how artificial intelligence (AI) and machine learning (ML) are being integrated into remote sensing–based tropical forest monitoring to address these structural constraints. Using a semi-systematic synthesis of peer-reviewed studies, complemented by operational platforms and grey literature, the review assesses AI/ML approaches, remote sensing datasets, and applications relevant to national and large-scale monitoring. Evidence is synthesized across five analytical dimensions: AI/ML model families and workflows, multi-sensor datasets and training resources, operational monitoring platforms, application domains (including deforestation, degradation, and biomass/carbon estimation), and cross-cutting technical, institutional, and governance barriers. The review finds that AI/ML-enabled remote sensing, particularly those combining optical, radar, and LiDAR time series within cloud-based platforms, has substantially improved the automation, scalability, and speed of tropical forest monitoring. However, effective and equitable adoption remains constrained by limitations in training and validation data, dependence on proprietary platforms and data, uneven technical capacity, and unresolved governance and ethical challenges. Emerging solutions, including open and representative training datasets, platform-agnostic processing infrastructures, long-term capacity building, and inclusive data-governance frameworks, are identified as critical enablers of credible and nationally owned AI/ML-enabled forest-monitoring systems. The review highlights that AI/ML can play a transformative role in supporting climate mitigation, biodiversity conservation, and informed decision-making. This potential, however, depends on transparent data governance arrangements, long-term capacity building, and platform-agnostic infrastructures that support national ownership. Full article

Heavy metals including mercury (Hg), lead (Pb), cadmium (Cd), and arsenic (As) remain significant global toxins due to their environmental persistence, widespread anthropogenic release, and serious biological effects. This review consolidates current understanding of their natural and industrial sources, environmental cycling, human exposure routes, and population-level vulnerabilities. It covers their toxicokinetics and toxicodynamics, emphasizing species-specific absorption, distribution, and injury mechanisms, including oxidative stress, thiol binding, mitochondrial dysfunction, endocrine disruption, and cancer risk. Clinical signs range from subtle neurocognitive impairment and kidney damage to severe acute poisoning. The review evaluates evidence-based approaches to risk assessment and biomonitoring, such as blood, urine, hair, and speciation tests, noting issues, including unvalidated provoked testing. Treatment focuses on removing exposure, providing nutritional support, and offering supportive care, with chelation therapy reserved for specific cases. It explains the chemistry, pharmacology, and roles of chelating agents—ALA, DMSA, DMPS, Cys, GSH, and physiologic thiols, comparing their effectiveness, limitations, and costs for various metals. Emerging therapies, precision toxicology, and public health strategies are discussed within a prevention-focused context. Unlike prior reviews focused primarily on toxic mechanisms or isolated clinical management, this review integrates mechanistic toxicology, biomarker interpretation and speciation, evidence-based clinical care, and ethical, cost-conscious decision-making within a single translational framework. This narrative review synthesizes foundational and contemporary literature published through 2025, with particular emphasis on studies published since 2000 that inform toxicokinetics, biomarker interpretation, diagnostics, clinical management, and prevention. Full article

This bibliometric study examines the role of ubiquitous computing and intelligent systems in the treatment of mental and neurological disorders. Ubiquitous computing integrates computational intelligence into everyday environments, enabling seamless monitoring and support of patients. Intelligent systems, including wearable devices, environmental sensors, and mobile health applications, collect real-time data on behavior, physiology, and environmental factors. These systems support early detection of symptom changes, adherence to treatment, and crisis prediction through context-aware analysis. Artificial intelligence (AI) processes the collected data to generate personalized therapeutic feedback and notify healthcare providers when intervention is needed. In mental health care, intelligent environments can monitor mood, sleep, and social interaction patterns, providing valuable objective information about mental health status. In the case of neurological conditions such as Parkinson’s disease or epilepsy, intelligent systems facilitate movement tracking, seizure detection, and cognitive assessment outside of the clinical setting. Integration with electronic health records and telemedicine platforms ensures coordinated and responsive care. Ethical design, privacy protection, and patient consent remain key to successful implementation. In this way, ubiquitous computing is transforming care models by increasing autonomy, precision, and continuity in the treatment of complex neurodegenerative diseases, including those related to neurodegeneration in aging. Full article