Search Results (114)

The pedagogical efficacy of artificial intelligence (AI) technologies in education heavily depends on cultural, technological, and cognitive contexts. Prior studies examined AI-driven learning outcomes without accounting for cultural variability or sufficiently anchoring their analyses in robust theoretical frameworks. The current study discusses the interconnection between AI technologies, learner competencies, and educational outcomes, in addition to the significance of digital and media literacy in secondary foreign language teaching. It employs Hofstede’s cultural dimensions theory, the technology acceptance model, and sociocultural learning theory to examine how AI technologies affect learning outcomes of English as a foreign language among Lebanese high school students. One hundred and eighty high school students in Mount Lebanon were given a 20-item survey using a quantitative research design. The results were analyzed using statistical tests and analyses in SPSS version 27.0.1. The findings indicate that AI technologies significantly enhance student learning outcomes: affective and motivational outcomes (45%), social and collaborative competencies (35%), and English language proficiency (accounting for 43% of variance). Furthermore, these relationships are strongly moderated by digital and media literacy, which increases the beneficial effects of AI on learning outcomes. The findings also show that students’ opinions, engagement, and acceptance of AI-supported language learning are influenced by cultural traits. Full article

To broaden the application of biomethanation for energy storage and renewable integration, this study investigates the performance of a trickle-bed reactor (TBR) for hydrogen (H₂) utilisation in biogas upgrading, using both pure Carbon dioxide (CO₂) and biogas-derived CO₂ as substrates for methane (CH₄) production. Renewable sources such as wind and solar are inherently variable, increasing the need for scalable storage solutions. Converting surplus electricity into H₂ and CH₄ via biological methanation offers an efficient and safer alternative to direct H₂ storage. By reducing CO₂ produced by biogas plants, methanogenic archaea produce CH₄, enabling H₂ valorisation and enhanced biogas yields. This study demonstrates that TBR technology can achieve CH₄ formation rates up to 15 L-CH₄/L-reactor/day under optimised conditions. Siporax carrier material supported dense biofilm formation and effective gas–liquid mass transfer, facilitating high conversion efficiency. The system showed operational robustness, with rapid recovery after prolonged idle periods and stable production rates of 10–12 L-CH₄/L/day. Wastewater was used as a realistic medium to assess reactor performance under complex, variable conditions. Reactor design focused primarily on enhancing gas–liquid mass transfer and supporting sustained microbial activity through adequate nutrient supply, ensuring sufficient buffer capacity to maintain pH stability. These results demonstrate the potential of TBR-based systems for high-rate, stable biomethanation and highlight their applicability in future energy infrastructures for integrating H₂ through decentralised biogas upgrading. Full article

Student employment has become an increasingly common feature of higher education, yet research on international students has predominantly approached paid work as an economic necessity. This article examines student employment as a culturally embedded social practice among international students in Hungary, focusing on employment patterns and cultural value orientations. The study applies a mixed-methods design, combining a focus group interview with an online questionnaire survey conducted among international students at a Hungarian university (N = 61). Cultural value orientations were measured using Hofstede’s Values Survey Module, and differences between working and non-working students were analyzed using inferential statistical methods. The results show that international students’ employment is dominated by flexible, low-entry-threshold jobs, particularly platform-based delivery work, while study-related or professional positions remain less common and are associated with higher income levels. Employment participation was significantly related to gender and academic year, with male students and those in higher years of study being more likely to work. Regarding cultural value orientations, a statistically significant difference between working and non-working students emerged only along the masculinity–femininity dimension, with working students displaying more performance-oriented values. The findings highlight that international student employment is associated with both structural constraints and culturally grounded value orientations. Full article

Background: Antimicrobial consumption (AMC) varies widely across European countries, and cross-national studies have linked this variation to cultural values. However, two critical gaps remain: it is unclear whether these associations differ between community and hospital sectors or across antimicrobial classes. This study directly tests these differences. Methods: We analysed country-level AMC data from the European Centre for Disease Prevention and Control for EU/EEA countries, combining sector-specific (community, hospital) and Anatomical Therapeutic Chemical (ATC) group-specific data. Spearman’s rank correlation coefficients (ρ) were calculated between Hofstede’s cultural dimensions and AMC. We compared correlations across sectors within ATC groups, and between community antibacterials for systemic use (J01) and other community medicine classes, using differences in correlations (Δρ). Uncertainty was assessed with non-parametric bootstrap 95% confidence intervals and paired-label permutation tests, with false discovery rate control. Sensitivity analyses included leave-one-country-out checks and replication using Kendall’s τ-b. Results: Cultural values, especially Power Distance Index (PDI) and Uncertainty Avoidance Index (UAI), were more strongly associated with community antibiotic use than with hospital antibiotic use or other community medicine groups. PDI and UAI showed significantly stronger correlations with community J01 use than with hospital J01 use and with several other community ATC groups. These patterns were robust in sensitivity analyses. Conclusions: The national cultural context appears more closely related to community antibiotic use than to hospital use or other community medicines, particularly for PDI and UAI. This demonstrates that cultural drivers of AMC are context-specific, necessitating stewardship strategies tailored to community settings to address norms around hierarchy and uncertainty. Full article

Sustainable service excellence in globalized industries requires organizations to develop workforce capabilities that support long-term relationship-building, cultural respect, and effective cross-cultural communication. This study examines how cultural intelligence functions as a mechanism for sustainable cross-cultural workforce development by investigating relationships among individual cultural values, cultural intelligence dimensions, and influence tactics among airline cabin crew members. Integrating Hofstede’s cultural dimensions framework, Ang and colleagues’ cultural intelligence model, and Yukl’s influence tactics taxonomy, we test a comprehensive mediation model using survey data from six hundred and sixty-three cabin crew members employed by international airlines operating in Turkey. The findings reveal that collectivism, long-term orientation, and uncertainty avoidance positively predict cultural intelligence development, creating foundations for sustainable cross-cultural competence. Cultural intelligence dimensions demonstrate differentiated effects on influence tactics, with metacognitive and behavioral cultural intelligence enhancing rational persuasion, behavioral cultural intelligence exclusively predicting relational tactics, and complex competitive mediation patterns for coercive tactics wherein motivational cultural intelligence reduces pressure-based influence while cognitive and behavioral dimensions increase strategic assertiveness. Cultural values directly influence tactics beyond cultural intelligence effects, with uncertainty avoidance most strongly predicting both rational and relational approaches that support relationship sustainability, while masculinity and power distance drive coercive tactics that may undermine long-term service relationships. These findings demonstrate that cultural intelligence functions as a multidimensional mediating mechanism with sometimes opposing effects, challenging assumptions that cross-cultural competencies uniformly produce sustainable outcomes. The research contributes to sustainable human resource management theory by illuminating how cultural socialization influences behavioral outcomes through complex psychological pathways, while offering practical guidance for aviation industry recruitment, training, and performance management systems seeking to build sustainable cross-cultural service capabilities. By revealing that certain cultural intelligence dimensions can enable both relationship-building and strategic coercion, the study highlights the importance of coupling cross-cultural skill development with ethical frameworks and motivational engagement to ensure that enhanced cultural capabilities support rather than undermine sustainable, respectful cross-cultural service relationships. Full article

Classroom management is a crucial aspect of effective teaching. However, little is known about how teachers’ approaches vary across countries. This study identified classroom management profiles using data from the OECD’s Teaching and Learning International Survey in five countries: Brazil, Canada (Alberta), Japan, Portugal, and South Africa. We applied latent class analysis (LCA) to four behavioral indicators, testing structural invariance and exploring associations with teacher characteristics and cultural dimensions. Three profiles emerged: Rule-Enforcing, Rule-Balanced, and Rule-Avoidant, which were structurally invariant across countries but varied in prevalence. Rule-Enforcing teachers reported the highest classroom management self-efficacy, whereas Rule-Avoidant teachers reported the lowest, with differences also observed in instructional and engagement efficacy. Cross-national variation in profile prevalence aligned descriptively with Hofstede’s cultural values, suggesting that cultural context shapes how universal management dimensions are enacted. These findings support the notion that classroom management is a universal construct shaped by significant national and cultural specificities. Full article

This study challenges the traditional perception of cultural values as uniform at the national level, particularly in light of globalization and demographic changes that reveal substantial intra-nation diversity. Utilizing a person-centered approach through Latent Profile Analysis (LPA), the research synthesizes Schwartz’s value orientations and Hofstede’s cultural dimensions to analyze data from 595 respondents in the United States, exemplifying a multicultural diverse society. The findings indicate that cultural value profiles primarily cluster around hierarchy and power distance, reflecting sociocultural attitudes toward authority and relational dynamics relevant to current social and political contexts. Notably, individual-level analysis reveals significant variations in how cultural values are internalized and enacted, suggesting that these values influence personal behavior rather than merely serving as collective descriptors. The study emphasizes the coexistence of conflicting cultural and value orientations within an individual and highlights the need to consider individual differences in cultural analysis. While the research contributes valuable insights into cultural psychology, the research is limited by its cross-sectional design and focus on a single nation, suggesting the need for future studies to adopt longitudinal and cross-national approaches. This research advances a more nuanced understanding of cultural values, with implications for management, policymaking, and education in multicultural societies. Full article

Purpose: This study investigated the attributes of confession pages on Facebook, their role within social networks, and their impact on society. It also explored their defining traits, the need for confession pages and the effects of anonymity. Methodology: The research methodology involved coding 1280 posts extracted from select pages, and semi-structured in-depth interviews with 15 prominent followers. Findings: Anonymity was found to be important because it helps individuals avoid social repercussions. Prominent recurring themes included formal behavior, relationships, and sexuality, topics that frequently involve social sanctions and penalties. The study also underscored the sense of community fostered by interaction between writers posting on confession pages and readers of these posts. The current study suggests that confession pages reflect society-level value preferences that shape interaction on social media according to Hofstede’s framework. Moreover, different confession groups serve to satisfy different needs, aligning with the theory of uses and gratifications in communication media. Practical implications: Engagement was shown by readers who extended offers to help and provided suggestions to support authors facing different challenges. Social implications: The motivations of anonymity for contributors to communities fostered through writer–reader interactions on the platform. Value: An in-depth examination of confession within contemporary society, redefining the contemporary landscape of confession, shedding light on its various perspectives within the public internet sphere, and thus contributing to comprehension of the different needs for anonymous expression. Full article

This research aims to evaluate and highlight the potential mesostructured architecture of established behaviours and operational practices based on the working model change imposed by the pandemic emergency in the public sector. After the intervention of an exogenous shock, the readiness, perceived usefulness and ease-of-use of technologies made the Technology Acceptance Model [TAM] verifiable. Concurrently, it is also possible to verify the Theory of Planned Behaviour [TPB] in the motivation and intention to change employees’ working habits under the lens of complexity and urgency, involving a From Knowledge To Knowledge Strategy [FKTKS]. The research protocol encompasses semi-structured interviews with public managers in Italy, alongside a perceptual and sentiment trend analysis of 70 public employees [35 females and 35 males] regarding their sentiments on digital transition and smart/hybrid working habits before, during, and after the pandemic. In the public sector, change is perceived as a shock-generative tension. In this way, the research aims to answer the genderised issue related to the perception and the persistence of using digital tools in the workplace during the post-urgency period as a regular habit based on perceived usefulness and ease-of-use. The study highlights a gender-specific trend in the use of the smart/hybrid working model after the health emergency. This propensity may also be attributable to the gender traits defined by Hofstede, within whose paradigm the interpretative dynamic provided is embedded. The during-COVID-19 acceptance and usage behaviours define an element related to masculinity because of its urgency and pressing deadlines. In contrast, endurance connects to femininity, emphasising resilience and long-term goals. This approach prioritises resilience and comprehensive well-being, focusing on achieving a good work–life balance [WLB] rather than just addressing immediate issues. Full article

Large language-model chatbots such as ChatGPT and DeepSeek are quickly gaining traction as an easy, first-stop tool for trip planning because they offer instant, conversational advice that once required sifting through multiple websites or guidebooks. Yet little is known about the biases that shape the destination suggestions these systems provide. This study conducts a controlled, persona-based audit of the two models, generating 6480 recommendations for 216 traveller profiles that vary by origin country, age, gender identity and trip theme. Six observable bias families (popularity, geographic, cultural, stereotype, demographic and reinforcement) are quantified using tourism rankings, Hofstede scores, a 150-term cliché lexicon and information-theoretic distance measures. Findings reveal measurable bias in every bias category. DeepSeek is more likely than ChatGPT to suggest off-list cities and recommends domestic travel more often, while both models still favour mainstream destinations. DeepSeek also points users toward culturally more distant destinations on all six Hofstede dimensions and employs a denser, superlative-heavy cliché register; ChatGPT shows wider lexical variety but remains strongly promotional. Demographic analysis uncovers moderate gender gaps and extreme divergence for non-binary personas, tempered by a “protective” tendency to guide non-binary travellers toward countries with higher LGBTQI acceptance. Reinforcement bias is minimal, with over 90 percent of follow-up suggestions being novel in both systems. These results confirm that unconstrained LLMs are not neutral filters but active amplifiers of structural imbalances. The paper proposes a public-interest re-ranking layer, hosted by a body such as UN Tourism, that balances exposure fairness, seasonality smoothing, low-carbon routing, cultural congruence, safety safeguards and stereotype penalties, transforming conversational AI from an opaque gatekeeper into a sustainability-oriented travel recommendation tool. Full article

This study develops and empirically validates a framework integrating cultural factors into sustainable supply chain management (SSCM) for emerging economies. We introduce the Cultural Affinity Index (CAI), a multi-dimensional construct quantifying cultural compatibility between supply chain partners based on language compatibility, regional trust, trade networks, and historical trade patterns. Using publicly available data from UN COMTRADE, the World Bank, and Hofstede Insights, we analyze 850 supplier–manufacturer dyads across five Southeast Asian countries (2019–2023). Through Monte Carlo simulation with empirically calibrated parameters, we demonstrate that high cultural affinity (CAI > 0.7) shows positive associations with economic performance (+18.0%), environmental compliance (+12%), and social sustainability (+32%) compared to baseline scenarios. We test both linear and interaction models, finding that language compatibility and regional trust exhibit synergistic effects ($\beta$ = 0.15, p < 0.01). Multi-objective optimization reveals Pareto-optimal solutions achieving simultaneous improvements across all triple bottom line dimensions. Sensitivity analysis confirms robustness across varying cultural weights (±20%) and institutional contexts. The framework’s effectiveness varies by institutional quality, with stronger associations in weaker institutional environments (correlation = −0.92). While focused on manufacturing, we discuss adaptations for service sectors. This research provides both theoretical contributions to the SSCM literature and practical tools for organizations managing culturally diverse supply chains in emerging markets. Full article

This study proposes and validates a culturally responsive instrument for assessing Student Experience (SX) in Higher Education Institutions (HEIs). Guided by Customer Experience (CX) theory and Hofstede’s cultural framework, we drafted a thirty-item scale: nine educational, seven social, three personal, and twelve cultural items spanning Indulgence–Restraint, Individualism–Collectivism, Masculinity–Femininity, Uncertainty Avoidance, Long- versus Short-Term Orientation, and Power Distance. Undergraduate respondents from universities with contrasting cultural profiles completed the survey. Confirmatory factor analyses affirmed a three-dimensional SX structure (Educational, Social, Personal) and six first-order cultural dimensions. A hierarchical second-order Structural Equation Model (SEM) linked the higher-order construct Cultural Aspects (CA) to the higher-order construct SX. The path from CA to SX emerged positive and statistically relevant, indicating that national-culture orientations systematically color students’ cognitive, affective, and behavioral evaluations of institutional touchpoints. The scale enables researchers and academic managers to pinpoint SX gaps, benchmark performance internationally, and design culturally congruent and sustainability-aligned interventions. The article deepens theoretical understanding of how culture shapes service perceptions in global HEIs by explicitly integrating cultural theory and cultural studies into SX evaluation. Full article

In this study, we examine banks’ sustainability orientations (SOs) in the Baltic region, focusing on how institutional, stakeholder, national culture, and leadership factors influence strategic alignment with the Sustainable Development Goals (SDGs). We assess how Baltic banks integrate sustainable development using a bibliometric review, financial performance analysis, Spearman’s rank correlation, and content analysis of sustainability-related disclosures for 2023, and interpret Hofstede’s cultural dimensions of the Baltic countries alongside these results. Our bibliometric review reveals limited research on SO and SD in banking, with a gradual annual increase of 14.8%. Our content analysis findings suggest that smaller banks are more broadly aligned with the SDGs; however, 36.4% of the largest banks in the region did not have a dedicated sustainability report a year before ESRS and CSRD requirements became mandatory. Notably, the reporting approach shows no statistically significant correlation with assets, size, global/local coverage, or the number of aligned SDGs. Furthermore, our content analysis findings reveal a persistent sustainability paradox: while economic and environmental goals are strategically prioritised, social SDGs are significantly underrepresented. We propose that this reflects a lack of demand for socially sustainable development rooted in regional contexts and national culture, which shape SO and organisational and leadership responses. Full article

Cultural factors shape students’ expectations and perceptions within diverse educational settings. The perceived quality of a Higher Education Institution (HEI) is crucial to its success, with student satisfaction determined mainly by their overall experiences. The concept of Student eXperience (SX) can be analyzed through the lens of Customer eXperience (CX) from a Human–Computer Interaction (HCI) perspective, positioning students as the “customers” of the institution. SX encompasses academic and physical interactions and students’ emotional, social, and psychological responses toward an institution’s systems, products, and services. By accounting for factors such as emotions, socioeconomic status, disabilities, and, importantly, cultural background, SX provides a comprehensive measure of student experiences. Building upon our previous SX model and Hofstede’s national culture model, we have developed a Student eXperience evaluation methodology that serves as a diagnostic tool to assess both student satisfaction and how effectively HEIs serve a diverse student population. This methodology ensures that all students, regardless of their background, are considered in the evaluation process, facilitating the early identification of institutional strengths and weaknesses. Incorporating cultural aspects into the assessment delivers more precise results. Furthermore, our approach supports HEIs in promoting equity, diversity, and inclusion by addressing the needs of minority students and students with disabilities, as well as reducing gender disparities. These objectives align with UNESCO’s Sustainable Development Goals, contributing to fostering an equitable learning environment. By adopting such inclusive evaluation practices, HEIs can enhance the perceived quality of education and their responsiveness to the needs of an increasingly multicultural student body. Full article

Purpose: This study aims to create a deep learning (DL) model capable of accurately delineating the ventricles, and by extension, the periventricular space (PVS), following the 2021 EPTN Neuro-Oncology Atlas guidelines on T1-weighted contrast-enhanced MRI scans (T1CE). The performance of this DL model was quantitatively and qualitatively compared with an off-the-shelf model. Materials and Methods: An nnU-Net was trained for ventricle segmentation using both CT and T1CE MRI images from 78 patients. Its performance was compared to that of a publicly available pretrained segmentation model, SynthSeg. The evaluation was conducted on both internal (N = 18) and external (n = 18) test sets, with each consisting of paired CT and T1CE MRI images and expert-delineated ground truths (GTs). Segmentation accuracy was assessed using the volumetric Dice Similarity Coefficient (DSC), 95th percentile Hausdorff distance (HD95), surface DSC, and added path length (APL). Additionally, a local evaluation of ventricle segmentations quantified differences between manual and automatic segmentations across both test sets. All segmentations were scored by radiotherapy technicians for clinical acceptability using a 4-point Likert scale. Results: The nnU-Net significantly outperformed the SynthSeg model on the internal test dataset in terms of median [range] DSC, 0.93 [0.86–0.95] vs. 0.85 [0.67–0.91], HD95, 0.9 [0.7–2.5] mm vs. 2.2 [1.7–4.8] mm, surface DSC, 0.97 [0.90–0.98] vs. 0.84 [0.70–0.89], and APL, 876 [407–1298] mm vs. 2809 [2311–3622] mm, all with p < 0.001. No significant differences in these metrics were found in the external test set. However clinical ratings favored nnU-Net segmentations on the internal and external test sets. In addition, the nnU-Net had higher clinical ratings than the GT delineation on the internal and external test set. Conclusions: The nnU-Net model outperformed the SynthSeg model on the internal dataset in both segmentation metrics and clinician ratings. While segmentation metrics showed no significant differences between the models on the external set, clinician ratings favored nnU-Net, suggesting enhanced clinical acceptability. This suggests that nnU-Net could contribute to more time-efficient and streamlined radiotherapy planning workflows. Full article