Search Results (2,830)

This study examined how perceived social media affordances, self-presentation, and online engagement collectively shape experiences of social validation among Nigerian youths within an integrated framework that combines Affordance theory, Goffman’s Dramaturgical perspectives, and Uses and Gratifications. Using a quantitative survey of 480 active social media users across platforms (Facebook, Instagram, TikTok, and X), data were analysed using descriptive statistics, Pearson correlations, regression, and regression-based sequential mediation modelling. Our findings indicate that perceived social media affordances significantly predict self-presentation behaviours (β = 0.79, p < 0.001), self-presentation significantly predicts online engagement (β = 0.43, p < 0.001); and online engagement predicts perceived social validation (β = 051, p < 0.001). Our findings also reveal that self-presentation and online engagement jointly and sequentially mediate the relationship between perceived affordances and perceived social media validation, with a significant indirect effect (β = 0.13, 95% CI [0.09, 0.19]) and a non-significant direct path from affordances to validation. Within a connectivity-constrained environment of Nigerian youths, our findings support a process-based understanding of digital interaction, showing how technological affordances are translated into social outcomes via structured, theoretically grounded user practices. Apart from validation emerging as a salient gratification, the study noted other motivational cues (sociability, identity expression, and information seeking) behind youth engagement with social media, suggesting that validation is just one of many reasons underlying youth social media use. The study contributes to Global Majority Media scholarship by providing a theoretically integrated process-based framework and a mechanism-oriented narrative of social media use in a non-Western setting. Full article

This study aims to identify and synthesize the major global trends that shaped 2025 by applying the DeflyCompass methodology to a curated corpus of strategic foresight reports. The study synthesizes insights from 23 strategic reports published by leading international organizations, including the World Economic Forum, Accenture, Euromonitor, and major technology firms. Methodologically, DeflyCompass operationalizes a structured hybrid human–AI pipeline comprising the deployment of multi-agent AI systems, automated knowledge graph construction, semantic clustering, and hybrid human–AI validation processes, reducing an initial set of 816 preliminary signals to a validated catalog of 50 high-priority trends across six PESTEL domains: Political, Economic, Social, Technological, Environmental, and Legal/Governance. Key findings indicate that artificial intelligence functions as a systemic enabling technology across all domains, climate and sustainability imperatives permeate multiple domains, geopolitical fragmentation introduces systemic tension, and trust deficits emerge as a critical vulnerability. The study contributes a replicable and scalable framework for global-level strategic foresight that operationalizes human–AI integration within a rigorous expert-driven validation process, complementing existing hybrid analytical approaches in the literature. Implications extend to decision-making in technology governance, sustainability strategy, social adaptation, and scenario planning, highlighting the necessity of integrating AI augmentation with human expertise for effective future-oriented planning. Full article

Oilfield worksites and the communities shaped by them are increasingly recognized as gendered spaces in which rotational labor, contractor hierarchies, and production imperatives can reshape norms of accountability and consent. This scoping review synthesizes conceptualizations of oilfield masculinities in scholarship on oil and gas extraction and examines their links to gendered harm, moral strain, and institutional accountability. Following PRISMA-ScR guidance, multidisciplinary databases were searched for English-language publications (2000–March 2024); eighteen sources met the inclusion criteria. A supplementary media scan (2000–2025) was conducted to contextualize cultural narratives surrounding oilfield labor. The synthesis identifies recurring themes, including frontier and breadwinner masculinities, emerging safety-oriented masculinities, gendered workplace exclusion, and the relational impacts of rotational absence and reintegration. Across studies, harms are most consistently described as patterned outcomes of work organization and fragmented governance rather than isolated incidents. Media representations frequently amplify heroism and endurance while minimizing institutional responsibility. Full article

Global environmental norms increasingly shape commodity governance in the Global South, with the EU Deforestation-Free Regulation (EUDR) representing a prominent attempt to govern land-based products through extraterritorial sustainability criteria. This study examines how such norms are received, reinterpreted, negotiated, and resisted in Indonesia’s palm oil sector, focusing on smallholder-dominated value chains in Serdang Bedagai and Simalungun, North Sumatra. Centered on everyday resistance and policy decoupling as its core interpretive lenses, and drawing on habitus as a supporting concept, the study employs qualitative fieldwork, in-depth interviews, field observations, and critical discourse analysis to investigate tensions between deforestation-free supply chain expectations and local realities marked by fragmented landholdings, informal tenure, intermediary dependence, and cashflow-oriented livelihood strategies. The findings show that the EUDR is widely perceived not as a sustainability opportunity, but as an externally imposed regulatory pressure that threatens income stability and market access. Local actors respond through discursive reframing, continued reliance on informal trading practices, and partial or symbolic implementation of legality and traceability requirements. The study argues that inclusive deforestation-free governance requires differentiated obligations, transitional legality pathways, and cooperative-based traceability mechanisms that better align global norms with local institutional capacity and livelihood structures. Full article

Virtual reality (VR) has been increasingly adopted as a digital tool in rehabilitation for balance training, coordination improvement, and motor recovery, yet the literature remains dispersed across clinical rehabilitation, exercise-based interventions, and broader motor-related applications. This fragmentation makes it difficult to determine how the field has evolved and where research emphasis has shifted. This study mapped the research landscape and thematic evolution of VR for balance, coordination, and motor rehabilitation using bibliometric analysis and topic modeling. A total of 1258 articles indexed in the Web of Science Core Collection from 2011 to 2025 were analyzed. Only English language articles and reviews relevant to VR-based balance, coordination, or motor rehabilitation research were included, yielding a final dataset of 1258 publications. CiteSpace and VOSviewer were used to examine keyword co-occurrence, clustering patterns, and temporal trends, while Latent Dirichlet Allocation (LDA) was applied to identify latent themes and their temporal dynamics. The field has moved beyond early feasibility testing toward a more differentiated landscape shaped by distinct clinical targets, population groups, and training purposes. Seven recurring themes were identified, including vestibular rehabilitation and immersive training, post-stroke upper-limb rehabilitation, efficacy and adverse-effect assessment, balance and gait training interventions, evidence synthesis and review-based evaluation, elderly exercise and cognitive interventions, and skill-oriented virtual task training with recent expansion toward broader population groups and task-specific applications beyond traditional rehabilitation settings. VR research on balance, coordination, and motor rehabilitation has evolved into a more thematically differentiated field rather than remaining a single rehabilitation-oriented domain. By combining bibliometric mapping with topic modeling, this study clarifies where evidence is concentrated and which thematic directions are gaining visibility, providing a clearer basis for future evidence synthesis and more comparable intervention reporting. Full article

Influencer marketing research has shown that source-related evaluations matter, yet less is known about how specific influencer cues are translated into consumer responses through differentiated internal psychological states. Drawing on the Stimulus–Organism–Response (S-O-R) framework, this study examines how influencer attractiveness and expertise shape consumer responses through parasocial interaction and trust. Attractiveness is conceptualized as a social-affective cue, whereas expertise is conceptualized as a competence-based cue. Parasocial interaction is modeled as a relational organismic state, and trust is modeled as a reliance-oriented organismic state. Survey data were collected from 532 Taiwanese social media users with prior experience following influencers and analyzed using partial least squares structural equation modeling (PLS-SEM). The results show that attractiveness positively predicts parasocial interaction, expertise positively predicts trust, and parasocial interaction further contributes to trust. Trust, in turn, positively influences loyalty, purchase intention, and recommendation intention, with the strongest effect observed for recommendation intention. These findings suggest that influencer effectiveness is better understood as a differentiated cue–mechanism–response process rather than as a generalized source-evaluation effect. By distinguishing attractiveness from expertise and by modeling parasocial interaction and trust as conceptually distinct but sequentially connected organismic states, this study provides a more precise S-O-R account of how influencer evaluations are translated into relational, transactional, and advocacy-oriented consumer responses. Full article

The growing integration of AI in business systems has intensified the need for empirical evidence on how organizational capability, governance orientation, and performance-related expectations shape AI adoption. This study examines how AI integration is perceived in terms of efficiency and effectiveness in relation to governance considerations and analyses the extent to which technological competence influences implementation intention. A quantitative research design was employed based on a structured questionnaire administered online to 248 respondents from diverse organizational contexts in Romania between September and December 2025, using a non-probabilistic sampling approach. The data collection procedure followed a voluntary participation approach, and the analysis includes descriptive statistics, reliability analysis, ANOVA, correlation analysis, and multiple regression. The findings indicate that AI is primarily associated with operational performance benefits, while governance-related perceptions play a contextual rather than a direct role in shaping implementation intention. Technological competence and resource adequacy emerge as the main factors associated with AI adoption, whereas favorable attitudes toward AI do not independently predict implementation decisions. The study contributes to the literature by introducing the Capability–Governance–Performance (CGP) framework as an integrative analytical perspective that explains how internal capabilities, governance considerations, and performance expectations jointly shape AI implementation intentions. It also provides empirical evidence from a transition-to-economic context, contributing to a more integrated understanding of AI adoption. Full article

Children’s everyday routes to school are increasingly recognised as important environments shaping physical and mental well-being. Yet, their emotional dimension remains insufficiently integrated into health-oriented urban design research, particularly in cities without formalised School Street policies. This study examines how children in Belgrade perceive and emotionally experience their everyday school routes and how such evidence can inform context-sensitive urban design. A mixed-method, child-centred participatory approach was applied with primary school pupils, combining participatory evaluation boards, cognitive route mapping, photo documentation, and facilitated classroom discussion. The material was analysed through qualitative coding, triangulation, and a health-oriented reinterpretation of the SCORELINE framework (h_SCORELINE). The findings reveal recurring stress nodes associated with traffic-dominated streets, complex crossings, obstructed sidewalks, and poorly legible route segments, which children linked to fear, discomfort, and insecurity. By contrast, greenery, recognisable landmarks, visually calm environments, and wider pedestrian spaces emerged as joy nodes associated with comfort, enjoyment, and emotional ease. These patterns suggest that children’s emotional-spatial evidence can enrich the assessment of school-route environments beyond conventional traffic indicators alone. By linking children’s lived experiences with health-oriented urban design, the study provides evidence-based support for the gradual introduction of School Streets in Belgrade. It offers a transferable framework for integrating child-centred experiential knowledge into healthier street design. Full article

This study examines the economic consequences associated with the mandatory adoption of International Financial Reporting Standards (IFRS) in the Iraqi banking sector. Motivated by growing evidence that the outcomes of IFRS adoption depend on institutional and market conditions, the study focuses on a bank-based emerging economy characterized by relatively underdeveloped capital markets and evolving enforcement mechanisms. Using a balanced panel of 24 banks listed on the Iraq Stock Exchange over the period 2014–2018, the analysis exploits the mandatory IFRS adoption in 2016 within a before–after regulatory framework. Panel regression techniques are employed to examine the associations between IFRS adoption and stock market liquidity, firm value, information asymmetry, and the cost of debt, while controlling for bank-specific characteristics and macroeconomic conditions. The results indicate that IFRS adoption is positively significantly associated with stock market liquidity, and negatively significantly associated with information asymmetry, consistent with improvements in the informational environment of Iraqi banks following enhanced disclosure and comparability. The findings also reveal a positive and significant relationship between IFRS adoption and the cost of debt, suggesting higher perceived financial risk by creditors. In contrast, no statistically significant association is observed between IFRS adoption and bank market valuation, highlighting the limited sensitivity of equity prices to accounting reforms in thin and institutionally constrained markets. Overall, the study contributes to the literature on the economic consequences of IFRS adoption by providing evidence from an underexplored emerging market and a highly regulated banking sector. The findings underscore the role of institutional context in shaping the outcomes of accounting standard convergence and offer policy-relevant insights for regulators and standard-setters in bank-oriented financial systems. Full article

Sustainability assessment of textile materials has traditionally relied on origin-based classifications and indicator-driven life cycle assessment (LCA), often treating sustainability as an inherent or material-intrinsic property. However, materials sharing similar biological origins or “bio-based” labels frequently exhibit substantially different sustainability outcomes when processing pathways, composite structures, and end-of-life (EoL) compatibility are taken into account. To address this limitation, this study develops a qualitative, multidimensional analytical framework that conceptualizes textile material sustainability as a pathway-dependent and system-mediated outcome rather than an inherent material attribute. The framework integrates four interrelated dimensions—renewability, process sustainability, EoL options, and material source—derived from a structured review of academic, policy, and technical literature. To demonstrate the analytical scope and internal logic of the framework, a selected set of 65 innovative textile materials was systematically analyzed using a three-tier qualitative coding scheme (favorable, conditional, and unfavorable) under conservative data validation criteria. The analysis shows that sustainability performance is primarily shaped by pathway configurations—particularly processing intensity, binder chemistry, and EoL compatibility—rather than material origin alone and that similar bio-based materials can exhibit fundamentally different sustainability profiles depending on these factors. By reframing sustainability from a material-centered perspective to a pathway-oriented and system-based perspective, the proposed framework provides a structured basis for integrating material innovation, process design, and end-of-life planning in sustainability-oriented textile research and development and establishes a conceptual foundation for future empirical and quantitative extensions. Full article

This paper examines the factors associated with valuation patterns in FinTech and RegTech mergers and acquisitions (M&A) using a global sample of 3739 completed transactions sourced from S&P Global Market Intelligence from 2008 to 2025. We develop and empirically validate an integrated theoretical framework combining digital platform theory, open innovation theory, and control-based theories of the firm. We test our five hypotheses using semi-log regression models with heteroskedasticity-robust standard errors. We document five main findings. First, full acquisitions are associated with valuation premiums nearly three times larger than traditional M&A control premiums in baseline specifications, which remain economically large (~188%) after correcting for sample selection. Second, cross-border transactions are associated with significantly higher valuations. Third, infrastructure-oriented FinTech and RegTech segments are valued more highly than consumer-facing segments. Fourth, transaction values increase systematically over time, consistent with declining uncertainty as the sector matures. Fifth, deal structure explains more variation in transaction values than temporal or geographic factors, reversing conventional valuation patterns observed in financial-sector M&A. We further document that tighter financing conditions significantly depress valuations, though the underlying structural drivers of the FinTech premium remain robust to these macroeconomic shifts. Our findings contribute to the banking and finance literature by demonstrating that M&A in FinTech and RegTech exhibit a distinct valuation regime shaped by digital platforms and innovation-driven control mechanisms. Full article

The overall swing dynamics of rigid slender payloads lifted in a vertical orientation deviate significantly from the ideal point-mass pendulum model, leading to severe performance degradation of feedforward control strategies designed based on this simplified model. This paper focuses on the bridge crane system and establishes a double-pendulum dynamic model that accounts for the payload’s mass distribution effect. To compensate for the theoretical error of the linearized model, a data-driven payload swing frequency correction strategy is proposed. Based on this corrected model, a dual-mode Zero Vibration Derivative (Corrected-Dual-ZVD) input shaping feedforward controller is designed. Simulations under eight typical operating conditions were conducted using the Matlab/Simulink control system simulation software. The results show that compared to the controller designed based on the traditional single-pendulum model, the proposed Corrected-Dual-ZVD controller, based on the corrected double-pendulum model, can significantly reduce the maximum residual swing angle of the payload. The average swing angle suppression rate reaches 68.9% across seven valid operating conditions, and it can reach 98.9% under the extreme condition of high speed and short rope length. When model parameters are subjected to ±10% disturbances, the proposed method demonstrates good robustness. Full article

Generative artificial intelligence (AI) is increasingly integrated into sustainability-oriented entrepreneurial practices, raising important questions about its role in shaping human creativity and innovation. This qualitative study examines how postgraduate social entrepreneurship students engage with generative AI during the creativity phase of sustainable startup development. Drawing on Amabile’s componential theory of creativity, this study explores how AI is perceived to relate to domain-relevant skills, creativity-relevant processes, task motivation, and social–contextual factors. Data were collected through an AI-assisted ideation task, followed by semi-structured interviews, and analyzed using reflexive thematic analysis. The findings reveal that generative AI was perceived as supporting information access and associative thinking, while being unable to replicate human intuition and the “aha” moment associated with deep creativity. Moreover, AI was perceived to have limited influence on intrinsic motivation, which remains driven by personal values and contextual responsibility. Socially, AI was consistently described as a tool rather than a teammate, with emotional responses regarded as superficial. The study further suggests that AI may be understood as a social–contextual condition and highlights a perceived trade-off between efficiency and creativity in AI-assisted ideation. These insights extend the application of creativity theory to AI-supported sustainability contexts and offer practical implications for fostering responsible, human-centered innovation in entrepreneurship education. Full article

Social media platforms have become critical communication environments during disasters, where individuals express emotions, share information, and engage in public discourse. These platforms also reflect heterogeneous communication patterns shaped by different actor groups. However, existing studies predominantly focus on emotion classification and often overlook the combined role of actor identity and conflict dynamics. To address this gap, this study proposes an integrated AI-based analytical framework for actor-aware emotion and conflict analysis in post-disaster social media. An expert-annotated Turkish tweet dataset was constructed based on Ekman’s emotion model, including anger, fear, sadness, happiness, and surprise, along with an additional irrelevant/off-topic category and conflict-level labels. A Transformer-based model (BERTurk) was fine-tuned for multi-class emotion classification. Experimental results show that the proposed model achieves strong classification performance, with an accuracy of 0.931 and an F1-score of 0.912, outperforming conventional machine learning and deep learning baselines. Actor-based analysis reveals systematic differences in emotional and conflict patterns across groups. Scientists, journalists, and individual users exhibit higher levels of conflict and more pronounced negative emotional expressions, whereas institutionally oriented actors display comparatively balanced and supportive communication patterns. In addition, a web-based decision support system was developed to enable interactive visualization and actor-level exploration of emotional and conflict dynamics. Overall, the proposed framework provides a scalable, analytically robust approach to understanding social media discourse in disaster contexts and offers practical implications for AI-driven crisis communication and decision-support systems. Full article

From hours spent in waiting rooms amidst uncertainty to the experience of recovering from medical treatments, the lived time of illness is marked by intervals of suspended sense. By disorienting our relation to the future, illness disrupts and reconfigures lived time from within, shaping how we navigate our intersubjective milieu and make sense of our unfolding lives. In this paper, we introduce the phenomenological concept of “protentional friction” as a way of understanding these experiences. Drawing upon Simone de Beauvoir’s work on subjectivity and becoming, alongside Henri Bergson’s and Eugène Minkowski’s emphasis on durée and élan, we demonstrate how protentional friction allows us to negotiate the tensions of our situation, orient ourselves toward the future through projects, and gear into the ongoing work of sense-making. As a counterbalance to normalizing cultural discourses surrounding illness, we reinterpret the idea of the “quotidian” as the everyday practice of sense-making to find and sustain an equilibrium. Full article