Search Results (4,758)

Many of life’s biggest dilemmas can be summed up as a tension between holding on and letting go. The very language evokes a notion of intentionality which, for the most part, has evaded scientific understanding. How might we even get a window into it? Important insights have come from a seemingly simple task: wiggling one’s fingers to and fro to the beat of a metronome. As the metronome pace increases to some critical frequency, one coordinative pattern becomes unstable and switches spontaneously to another. Such transitions are typically preceded by critical fluctuations, a predicted feature of self-organization in complex, dynamical systems. Here we address the nature and source of these fluctuations, usually assumed to be: (1) random; (2) of external origin; and (3) of fixed magnitude. We performed an experiment in which participants were instructed to oscillate their fingers in either an in-phase or anti-phase pattern in time with a metronome and instructed them to either “hold-on” or “let-go” should they feel the pattern begin to change, yielding a 2 by 2 within-subjects design. We observed that as the metronome frequency was increased from 1.00 to 3.00 Hz, fluctuations in the relative phase between the fingers were significantly altered both by the starting coordinative pattern as well as the participant’s intention to “hold it on” or “let it go”. Specifically, the intention to hold on to the anti-phase pattern delayed the spontaneous transition to in-phase, an effect that was paired with increased fluctuations beyond the critical frequency. These observations were analyzed under the extended Haken–Kelso–Bunz (HKB) model which describes the non-linear stochastic dynamics of the order parameter (relative phase) as a gradient descent on a certain potential. Our analysis, in line with experimental results, suggests that intention transforms the HKB potential not only by stabilizing unstable coordination states but also (paradoxically) by increasing fluctuations around them. Such findings may offer new interpretative light on the relation between intention and fluctuations in the coordination dynamics of living things. Full article

Mobile payment systems are widely viewed as a practical lever for sustainable financial inclusion in developing economies, with relevance to UN Sustainable Development Goals 1, 8, and 10. Yet in countries such as Egypt—where mobile penetration exceeds 95% but banking penetration remains below 35%—sustained engagement with these services lags policy expectations, suggesting that determinants beyond technology shape behavior. This study examines the determinants of behavioral intention and continued use of mobile payment among Egyptian users, and tests whether cultural factors dominate conventional technology-acceptance predictors in a collectivist, high-power-distance setting. A structured bilingual (Arabic–English) questionnaire measuring nine predictors across technology, psychological, and socio-cultural dimensions was administered to 200 active mobile-payment users in Egypt during January–February 2025. Hierarchical regression and mediation analysis (with Sobel/delta-method 95% confidence intervals as a robustness check) were used to examine direct effects on Behavioral Intention and continued use, and the mediating role of Behavioral Intention. Cultural Influence emerged as the strongest predictor of Behavioral Intention (β = 0.421, p < 0.001), followed by Facilitating Conditions (β = 0.282, p < 0.001); conventional TAM variables were not statistically significant. Cultural Influence retained a significant direct effect on continued use (β = 0.253, p < 0.01), indicating partial mediation. The findings support culture-sensitive approaches to technology adoption research and inform financial-inclusion policy in non-Western contexts. Limitations include the cross-sectional design and the convenience-based snowball sample of existing users. Full article

Organized after-school activities can play a vital role in supporting historically marginalized youth in science, technology, engineering, and mathematics (STEM), yet less is known about how culturally responsive practices—which are practices that integrate youths’ cultural backgrounds and lived experiences into learning—are enacted in math-focused learning spaces. Drawing on empowerment theory and critical youth empowerment frameworks, this qualitative study examines how culturally responsive practices foster empowerment among middle school students participating in a university-based after-school math enrichment program. Ninety-two students (M_age = 12.26 years; 47% girls; 86% Latine) from three under-resourced schools in Southern California participated in semi-structured interviews about moments when they felt empowered and what contributed to those experiences. Thematic analysis revealed that all four domains of culturally responsive practices helped promote empowerment: structured opportunities for contribution and leadership, caring relationships, cultural affirmation, and efforts to make real-world connections. In particular, students most frequently described structured opportunities for contribution and leadership, practices that centered their knowledge and voices, and relational climates characterized by care and high expectations. The findings suggest that in after-school STEM contexts, empowerment does not arise as an isolated individual trait but is part of a relational and context-dependent process that is supported by culturally responsive practices. These findings highlight how intentional, culturally responsive program design can advance both youth empowerment and equity-oriented STEM education. Full article

Large Language Models (LLMs) offer state-of-the-art performance in natural language understanding and generation tasks. However, the deployment of leading commercial models for specialized tasks, such as e-commerce, is often hindered by high computational costs, latency, and operational expenses. This paper investigates the viability of smaller, open-weight models as a resource-efficient alternative. We present a methodology for optimizing a one-billion-parameter Llama 3.2 model for multilingual e-commerce intent recognition. The model was fine-tuned using Quantized Low-Rank Adaptation (QLoRA) on a synthetically generated dataset designed to mimic real-world user queries. Subsequently, we applied post-training quantization techniques, creating GPU-optimized (GPTQ) and CPU-optimized (GGUF) versions. Our results demonstrate that the specialized 1B model achieves 98.8% accuracy, approaching the performance of the significantly larger GPT-4.1 model. A detailed performance analysis revealed critical, hardware-dependent trade-offs: while 4-bit GPTQ reduced VRAM usage by 41%, it paradoxically slowed inference by 82% on an older GPU architecture (NVIDIA T4) due to dequantization overhead. Conversely, GGUF formats on a CPU achieved a speedup of up to $4.3\times$ in inference throughput and up to a 72% reduction in RAM consumption compared to the FP16 baseline. We conclude that small, properly optimized open-weight models are not just a viable but a more suitable alternative for domain-specific applications, offering state-of-the-art accuracy at a fraction of the computational cost. Full article

This study systematically reviews 129 peer-reviewed empirical studies examining tourism and hospitality (T&H) students’ perceptions of their employment prospects and future career paths. A systematic review was conducted using the RePEc database, which provides comprehensive coverage of economics, tourism, and hospitality research, ensuring broad and interdisciplinary representation of relevant studies. By synthesizing evidence across three decades, the review identifies persistent and emerging themes shaping students’ career outlooks. Negative perceptions, particularly regarding pay, working hours, job security, and career progression, remain the most frequently reported concerns and are strongly associated with employment anxiety. At the same time, the analysis highlights a significant rise in entrepreneurial intentions after 2015, reflecting students’ growing preference for autonomy and innovation. Internships and real-world experiences consistently emerge as pivotal in shaping perceptions, either reinforcing commitment to the sector or exposing mismatches between expectations and workplace realities. The review further underscores the influence of cultural, social, and personal factors, including family background, gender norms, and self-efficacy, in shaping career decisions. This study contributes by offering a comprehensive thematic synthesis, identifying patterns and transitions over time, and outlining research gaps. The findings provide actionable insights for educators, industry practitioners, and policymakers seeking to strengthen career pathways and ensure the long-term sustainability of the T&H workforce. Full article

In recent years, digital technologies have been widely applied in the gig economy, and platform algorithms have become the core tool for managing gig workers. This study collected data through a multi-phase questionnaire survey and conducted empirical regression tests and fuzzy-set Qualitative Comparative Analysis (fsQCA). It explored how perceived algorithmic control affected gig workers’ turnover intention through psychological contract breach and perceived usefulness, analyzed the moderating role of time pressure, and investigated its relevant configurational pathways. The results indicated that perceived algorithmic control negatively affected gig workers’ turnover intention. Psychological contract breach and perceived usefulness both partially mediated the relationship between perceived algorithmic control and turnover intention. Time pressure negatively moderated the relationship between perceived algorithmic control and perceived usefulness, thereby weakening the indirect effect of perceived algorithmic control on turnover intention via perceived usefulness; however, it did not significantly moderate the relationship between perceived algorithmic control and psychological contract breach. Configurational analysis revealed that high psychological contract breach served as a core condition leading to turnover intention, and its combination with low perceived usefulness or low perceived algorithmic control constituted multiple pathways toward high turnover intention. This study extends the literature on the behavioral consequences of perceived algorithmic control and provides theoretical insights and practical implications for gig platforms seeking to optimize algorithm design, alleviate time pressure, and reduce worker turnover. Full article

Near-expired food has received increasing attention in recent years as an important way to reduce food waste and promote sustainable consumption. However, although consumers recognize its economic value and environmental significance, they still have concerns about its quality and potential risks. Drawing on social cognitive theory and social exchange theory, this study adopts a benefit–risk trade-off perspective to examine how personal and environmental factors influence purchase intention toward near-expired food through perceived benefits and perceived risks. Based on 547 valid questionnaires collected from Chinese consumers, this study employs PLS-SEM, multi-group analysis (MGA), and fuzzy-set qualitative comparative analysis (fsQCA) for empirical testing. The results show that personal norm and price discount significantly increase perceived benefits, whereas social image concern and product uncertainty significantly increase perceived risks. Perceived benefits have a significant positive effect on purchase intention, whereas perceived risks have a significant negative effect. The MGA results further show that purchase experience and income level lead to significant differences in consumers’ decision paths. The fsQCA results indicate that both high and non-high purchase intention can be formed through multiple distinct but equivalent paths. High purchase intention mainly follows two patterns, benefit-driven and cognitive trade-off. Non-high purchase intention is mainly characterized by benefit deficiency and risk interference. The findings provide implications for the marketing and risk management of near-expired food. Full article

Hybrid hydrogen energy storage systems are increasingly considered for renewable integration in rural and weak-grid contexts, yet much of the literature remains simulation-based, site-specific, or insufficiently explicit about control and operational performance. This paper examines a hybrid hydro–PV–battery–hydrogen system operated at the Agkistron Living Lab in Northern Greece and assesses the role of layered storage in renewable surplus valorization and resilience-oriented operation. This study combines a system architecture description, a supervisory energy management strategy based on Hybrid Automata, and analysis of field data under both grid-connected and intentional off-grid conditions. The installation integrates hydropower, photovoltaics, battery storage, alkaline electrolysis, hydrogen storage, and PEMFCs. The results show that during on-grid operation, the EMS prioritizes battery charging and then hydrogen production, enabling high renewable utilization and low curtailment while preparing reserves for outages. During a 48 h intentional islanding event, the battery and hydrogen pathway operated sequentially, achieving an autonomy index of 82%, compared with 36% for the battery-only benchmark. Although the hydrogen pathway showed lower round-trip efficiency than battery-only storage, it substantially extended off-grid autonomy and continuity of supply. The findings support hybrid battery–hydrogen storage as a transferable operating concept for rural systems where renewable surplus and resilience requirements coexist. Full article

The rapid development of the fintech sector has facilitated the emergence of digital multi-level marketing (MLM) schemes, raising concerns about investor protection. Despite extensive literature on MLM schemes and pyramid schemes, there remains a significant research gap regarding the psychological mechanisms and cognitive biases that drive investor participation behavior. This study investigates factors influencing Vietnamese female investors’ intention to participate in fintech MLM schemes, using Pi Network as a case study. Grounded in behavioral finance theories (Prospect Theory and Social Comparison Theory), the model empirically examines the impacts of herding bias and overconfidence bias, explaining participation intention through the mediating effect of the fear of missing out (FOMO) and perceived risk. A quantitative approach was employed using PLS-SEM analysis, with data collected from 264 female investors in Ho Chi Minh City. The results reveal that herding behavior and overconfidence significantly shape investors’ FOMO and perceived risk, with these biases significantly increasing FOMO and decreasing perceived risk. More importantly, these biases, mediated by FOMO and perceived risk, significantly shape participation intention in fintech MLM schemes. This study contributes empirical evidence showing the interaction between high social connectivity and cognitive-bias-driven vulnerabilities in a rapidly expanding and unregulated digital market such as Vietnam. This study has practical implications for policymakers and financial educators in protecting investors from financial schemes by monitoring social media to debunk “safety in numbers” narratives and prioritize the awareness of biases in financial education to mitigate impulse investments. Full article

Objective: This study aimed to compare the effectiveness of online cognitive behavioral therapy (CBT) delivered by an AI chatbot versus human peer counselors (participants were told it was AI) in reducing anxiety symptoms in young adults. Methods: Ninety young adults with mild-to-severe anxiety were randomized to a 4-week intervention of AI-CBT (n = 30), peer-counselor-CBT (n = 30), or a no-intervention control (n = 30). The primary outcome, anxiety, was assessed at baseline, mid-point, and post-intervention. Secondary outcomes (the self-efficacy for exercise, sleep quality), psychotherapy benefit, and qualitative user experiences were also evaluated. Results: Both AI and human-delivered interventions led to significant within-group reductions in anxiety (p < 0.05). However, in the primary intention-to-treat analysis, neither intervention demonstrated a statistically significant advantage over the no-intervention control group at post-intervention. A secondary per-protocol analysis suggested a benefit for the human-delivered intervention among study completers. Notably, participants in the AI group reported significantly lower perceived treatment benefit than the human group (p < 0.001). Qualitative analyses indicated that while AI was valued for accessibility and consistency, human intervention was perceived as more flexible in guidance, individualized, emotionally supportive, and conducive to deeper exploration. Conclusions: In this exploratory trial, both AI- and peer-counselor-CBT showed within-group promise, but the evidence does not support their efficacy over a no-intervention control. The AI’s limitations in providing flexible, emotionally supportive, and personalized interaction likely explain the efficacy gap observed between the two interventions. While AI may serve as a scalable support tool, claims of clinical efficacy require significant caution. These preliminary findings warrant replication in a prospectively registered confirmatory trial. Full article

Background: Healthcare chatbots have emerged as a promising application of artificial intelligence in healthcare, offering potential benefits in accessibility, efficiency, and patient engagement. However, despite their growing adoption, limited research has examined the factors that determine their success from the user’s perspective. Objective: This study aimed to evaluate the success of a health chatbot service by applying the updated DeLone and McLean Information Systems Success Model augmented with a trust construct, examining the effects of information quality, system quality, service quality, and trust on intention to use, user satisfaction, and net benefits. Methods: An online survey design was employed, utilizing a structured questionnaire with 28 items measuring seven constructs on a seven-point Likert scale. Data were collected electronically from residents of Saudi Arabia between July and September 2024 using convenience sampling. Eligible participants were adults aged 18 years or older who had previously used the health chatbot service. A total of 321 valid responses were obtained. Partial Least Squares Structural Equation (PLS-SEM) was conducted using SmartPLS 3.3 software for measurement and structural model analysis. Results: The measurement model demonstrated acceptable reliability and validity, with composite reliability values exceeding 0.90 and average variance extracted values above 0.70 for all constructs. Structural model analysis supported eight of ten hypotheses. Trust exhibited the strongest effect on intention to use (β = 0.359, p < 0.001), followed by system quality (β = 0.234, p < 0.001) and information quality (β = 0.147, p < 0.01). Intention to use significantly predicted user satisfaction (β = 0.620, p < 0.001) and net benefits (β = 0.278, p < 0.001). User satisfaction demonstrated a strong positive effect on net benefits (β = 0.610, p < 0.001). The model explained 67.6% of the variance in intention to use, 72.7% in user satisfaction, and 71.4% in net benefits. Conclusions: Trust emerged as the most influential factor affecting intention to use the healthcare chatbot service, underscoring its critical role in user acceptance of health chatbot services. Information quality, system quality, and service quality exerted small to moderate effects on behavioral outcomes. These findings suggest that healthcare organizations deploying chatbot services should prioritize building user trust alongside ensuring high system and information quality to maximize user satisfaction and realized net benefits. Full article

The adoption of artificial intelligence (AI)-enabled technologies and information technology (IT) systems in entrepreneurship education has accelerated alongside the digital transformation of higher education. With a particular focus on gender-related disparities, this study examines how digital business modeling tools influence students’ entrepreneurial intentions. It conceptualizes digital tools along a continuum, ranging from non-AI solutions to AI-embedded and fully AI-driven systems. Data from 440 students taking part in entrepreneurial workshops using the AI-enabled digital tool KABADA served as the basis for empirical investigation. Changes in entrepreneurial intention and its key antecedents—attitude toward entrepreneurship, subjective norms, and perceived behavioral control—are examined by comparing the pre-workshop and post-workshop groups using structural equation modeling. According to the findings, the KABADA workshop has a statistically significant positive indirect effect on entrepreneurial intention, which is mainly mediated by perceived behavioral control. Significant gender differences are revealed by multi-group analysis: for female students, the main factor influencing entrepreneurial intention is perceived behavioral control, while for male students, the main factor is attitude toward entrepreneurship. These results emphasize the significance of IT systems that integrate guided user engagement with AI-based analytics to improve entrepreneurial self-efficacy, especially among women. Full article

The development of sustainable tourism in rural areas brings new challenges in terms of innovation and social inclusion. In this context, this study examines the adoption of social innovation by managers of rural guesthouses in Morocco. The objective is to identify the factors that influence their intention to adopt such practices, which may strengthen local cohesion, enhance cultural resources, and meet visitors’ expectations regarding sustainability. The analysis draws on the conceptual framework of the diffusion of innovation, which allows for the exploration of perceptions related to the relative advantage, compatibility, ease of use, visibility, and trialability of innovative practices. The research is based on a questionnaire survey conducted with a sample of 174 managers. The data collected underwent confirmatory factor analysis to validate the theoretical dimensions of the model, and were then analyzed using an ordered Logit model to account for the ordinal nature of the dependent variable measuring the intention to adopt. The empirical results indicate that several perceived factors—namely the superiority of the innovation, its economic or symbolic benefits, its cultural compatibility, its simplicity of understanding and use, and the visibility of its effects—have a significant influence. Other dimensions, such as technical compatibility or risk perception, do not show a notable effect. The study also highlights the role of education level and gender in the propensity to adopt social innovation. Full article

Objectives: This study aims to characterize sexual assaults through the analysis of demographic, clinical, and medico-legal variables and to identify areas for improvement both in the care pathway and in the collection of information relevant to judicial proceedings. Methods: A retrospective review of injury reports issued by the reference hospital in Cantabria (northern Spain) between 2021 and 2024 was conducted. Variables related to the victim and the assault (including its temporal and spatial characteristics) were extracted, and both descriptive and analytical statistical methods were applied. Results: The results showed that 57% of reported sexual assaults occurred in a private residence, and in 68% of cases, the victim had voluntarily met with the aggressor. Temporally, incidents took place predominantly during early morning hours and on weekends, and most victims sought medical care within the first 24 h. Notably, 52% had consumed drugs or alcohol, 22% reported memory gaps suggestive of chemical submission, and victims who had consumed alcohol were less likely to express an intention to press charges (p = 0.005). In over half of the reports, the information provided was insufficient to properly interpret the results of biological trace analyses. Conclusions: Identifying common variables related to both the victims and the circumstances of sexual assault is essential for developing effective prevention and intervention strategies. Furthermore, the information to be included in injury reports for sexual assault should be standardized at the national level, as shortcomings in data collection during the initial medical assessment (which is highly relevant for judicial processes) highlight the need to raise awareness among emergency care professionals. Full article

Against the backdrop of the growing emphasis on cultural confidence and the continuous expansion of cultural consumption, how local museums effectively transform local cultural resources into cultural and creative consumption behavior has become an important research issue. Taking the Luoyang Museum as the empirical context, this study integrates Place Attachment Theory (PALT) with the Stimulus-Organism-Response (S-O-R) framework to construct a research model of “place attachment–cultural participation–perceived authenticity/experience satisfaction–behavioral intention.” Based on 182 valid samples, Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed for empirical analysis. The results indicate that place attachment significantly and positively influences cultural participation; cultural participation significantly and positively affects experience satisfaction, perceived authenticity, and behavioral intention; experience satisfaction significantly enhances perceived authenticity; and perceived authenticity significantly promotes behavioral intention. Further analysis reveals that cultural participation plays a significant mediating role between place attachment and experience satisfaction, perceived authenticity, and behavioral intention. Perceived authenticity serves as a key mediator between cultural participation, experience satisfaction, and behavioral intention. In addition, multiple serial mediation paths, such as “cultural participation–experience satisfaction–perceived authenticity–behavioral intention,” are found to be significant. The findings demonstrate that place attachment does not directly translate into cultural consumption behavior, but instead operates through cultural participation to activate authenticity perception and experiential evaluation, which in turn influence behavioral intention. This study enriches the application of Place Attachment Theory and the S-O-R framework in the context of museum cultural consumption and provides both theoretical support and practical implications for enhancing the transformation capacity of cultural and creative products in local museums. This study enriches the application of Place Attachment Theory and the S-O-R framework in museum cultural consumption research and provides theoretical support and practical implications for enhancing the transformation capacity of cultural and creative products in local museums, particularly in promoting sustainable cultural consumption. Full article