Search Results (2,094)

Despite the promise of human–AI interaction in enhancing learning outcomes, its contribution to fostering sustainable learning resilience, particularly in underdeveloped regions, remains insufficiently examined. Prior research has inadequately investigated the psychological processes underlying the relationship between human–AI interaction and the development of resilience. To address these gaps, this study adopts the Cognition–Affect–Conation (CAC) framework to explore how task–technology fit and system quality collectively shape the dynamics of sustainable learning resilience, mediated by perceived value and trust. Survey responses were collected from 617 students across 34 universities in Western China, using both online and offline methods. The findings indicate that task–technology fit and system quality substantially influence students’ perceptions of value and trust in human–AI interactions, which in turn strengthen their sustainable learning resilience. Additionally, these mechanisms exert a significant positive influence on different academic disciplines. This research advances the understanding of how human–AI interactions facilitate sustainable learning resilience and provides actionable insights for implementing equitable technology solutions in higher education, particularly in resource-constrained environments. Full article

Adolescents with LGBTQ+ parents and LGBTQ+ adolescents navigate unique social and identity-related challenges as compared to those without minoritized sexual and/or gender identities. Adolescents with LGBTQ+ parents (regardless of their own sexual or gender identity) and adolescents who personally identify as LGBTQ+ are distinct populations, though they sometimes overlap. Research on adolescents with LGBTQ+ parents has often focused on parent–adolescent relationships and family structures. How do friends help youth cope with identity-based minority stressors, like peer microaggressions, bullying, and exclusion, common for those with minoritized identities? Friendships are developmentally pivotal during adolescence, shaping social competence, identity exploration, and psychological adjustment. Grounded in ecological systems, social learning, and minority stress theories, we sought to understand how friendships relate to mental health and coping in adolescents with LGBTQ+ parents. This cross-sectional quantitative study included 98 adolescents (ages 12–19) with LGBTQ+ parents in the U.S., recruited via community sampling and Prolific. Higher-quality peer attachment, conceptualized by trust, communication, and alienation in close friendships, was associated with lower depression and greater social competence, but not associated with anxiety or adaptive coping (after accounting for avoidant coping). Avoidant coping was most strongly associated with poorer mental health. This study, with implications for practice, emphasizes the importance of peer relationships for adolescents with LGBTQ+ parents—particularly how high-quality friendships offer important possible protection via social competence and against depression—while also highlighting the complex interplay between friendships, coping, and adjustment. Full article

This research investigates the factors influencing the behavioral intention and actual use of e-wallets among Generation Z by extending the UTAUT3 model to include personal innovativeness and perceived security. The study employs a quantitative approach using Partial Least Squares Structural Equation Modeling (PLS-SEM). Data were collected from 535 Generation Z e-wallet users between 15 January and 28 February 2026. The results reveal that traditional determinants such as performance expectancy, effort expectancy, facilitating conditions, and hedonic motivation do not significantly influence behavioral intention in a mature digital environment. In contrast, social influence, price value, habit, personal innovativeness, and perceived security significantly shape users’ intentions. Furthermore, the findings indicate that behavioral intention fully mediates the relationship between personal innovativeness and perceived security with actual usage behavior. This suggests that although users may possess innovative tendencies and perceive strong security, these factors influence usage only through the formation of intention. The study also shows that Generation Z demonstrates a strong ability to manage financial activities independently within digital platforms, reflecting high levels of digital and financial literacy. At the same time, users remain highly aware of potential risks, particularly regarding data privacy and transaction security, which significantly affect their intention to adopt e-wallet services. Additionally, actual usage behavior is primarily driven by habit and behavioral intention, indicating routinized usage patterns. Overall, this study highlights the critical roles of trust, social influence, and behavioral reinforcement in explaining technology adoption among Generation Z. Full article

Live streaming e-commerce has emerged as a dominant force in electronic commerce. Although extensive research has examined service failures and recovery in conventional e-commerce environments, there is limited understanding of how buyers interpret and respond to service recovery information provided by streamers in live streaming contexts, where streamers fulfill dual roles as both idols and sellers. This study, grounded in signaling theory, investigates the relationships among buyers’ observation, interpretation, and feedback of service recovery information. Specifically, it aims to assess how buyers’ perceived justice regarding service recovery information affects their repeat purchase intentions following live streaming e-commerce failures. Meanwhile, this study elucidates the mediating role of trust in the streamer (idol role and seller role) and verifies whether responsibility attribution and product involvement have moderating effects on the effect of perceived justice. Employing PLS-SEM analysis, the study analyzes data from 401 buyers who have experienced service failures in live streaming e-commerce. The findings reveal that perceived justice positively influences repeat purchase intentions to a certain extent. Trust in the streamer mediates the link between perceived justice and repeat purchase intentions. The inhibiting moderation effect of responsibility attribution and product involvement is generally significant. This study contributes to the theoretical understanding of signaling theory by expanding the signaling model to encompass service recovery information in live streaming e-commerce. Furthermore, it provides practical guidance for live streaming e-commerce practitioners on managing service recovery information, including recommendations for the sequence of sending such information, enhancing its transmission, and improving its overall effectiveness. Full article

Throughout history, communities have experienced changes in their food culture and their cultural interactions and relationships with food. Weak relationships with food, and more widely with people through food, reduce the perceived cultural value of food and its role in a healthy lifestyle, which can lead to poor food-related health outcomes. This exploratory narrative review seeks to explore the extant literature as a grounding for empirical research focused on differentiating between food culture and the relational and cultural values associated with food, i.e., articulating the difference between value-based and values-based food networks. Terms emergent from the academic and grey literature were familial and cultural grounding of respect for food, through food and via food environments to develop relationships with food, trust and identity. The concepts of ‘food culture’ and an individual perceiving a ‘cultural value of food’ were found to be distinct, but not mutually exclusive. Alternative food networks (AFNs) were positioned as more able to facilitate the development of values-based food networks than conventional food systems. This work contributes to improving clarity of language when considering non-financial value and values associated with food. Full article

As digital technology has become increasingly integrated into rural governance and daily life in China, Internet use among rural residents exerts a multifaceted influence on their mental health. A key mechanism lies in its restructuring of the neighborhood social environment. Uncovering this mechanism is essential for understanding the theoretical and practical connections between rural social transformation and individual well-being in the digital age. This study applied a binary probit model to data from the 2020 China Family Panel Studies (CFPS) to examine the impact of Internet use on the mental health of rural residents. Mediation analysis was used to examine the role of the neighborhood social environment, and the conditional mixed process method was applied to address potential endogeneity issues. Empirical results demonstrate that access to the Internet, along with the breadth and depth of its use all significantly improve the mental health of rural residents. Internet use promotes mental health by strengthening neighborhood relationship and trust, whereas it also negatively affects mental health by suppressing neighborhood identity. Heterogeneity analyses reveal three key dimensions of variation. (1) By usage type: Activities such as gaming, short-video consumption, and WeChat communication show positive associations with mental health, whereas online shopping and learning exhibit non-significant effects. (2) By user group: The mental health benefits are more pronounced among women, less-educated individuals, and middle-aged to older adults. (3) By region: Positive associations are observed in central and western China, with the most substantial effect in the central region. This study elucidates the mechanism through which Internet use affects mental health: the restructuring of traditional, place-based social capital in rural neighborhoods. These findings offer robust empirical support for policies that integrate digital initiatives with the nurturing of local community bonds to improve rural mental health and foster livable and harmonious villages. Full article

Organizational commitment is crucial for employee retention and performance; however, little is known about how social and leadership resources translate into organizational commitment through routine learning behaviors. Based on the Conservation of Resources (COR) theory, this study explores how trust and leader’s vision of talent influence organizational commitment through three informal training formats: peer/supervisor coaching, knowledge sharing, and job rotation. Using data from the 2023 Korea Human Capital Enterprise Survey (N = 10,371), this study employs a generalized structural equation model that combines Bernoulli logit mediation equations with Gaussian identity outcome equations, along with the bootstrap method, to test the proposed mediation model. The results show that trust and leader’s vision of talent are positively correlated with organizational commitment, whereas knowledge sharing and job rotation significantly mediate these relationships. Peer/supervisor coaching shows no mediating effect. This study conceptualizes informal training as a mechanism through which workplace resources are implemented and translated into employee attitudes, thereby extending COR theory from resource acquisition and protection to resource utilization processes in everyday organizational contexts. The findings suggest that organizations should strengthen trust-based and development-oriented human resource practices to foster employee commitment. These implications extend beyond Korean firms to global HR practitioners seeking to build learning-supportive workplaces. Full article

This study addresses supply uncertainty in the transportation and production of agricultural products within e-commerce-driven supply chains by developing a stochastic supply chain framework. By embedding an endogenous trust-based punishment mechanism, we characterize the strategic interplay between relational governance and operational decisions. In the single-period setting, higher retailer trust leads to larger order quantities while reducing the supplier’s optimal supply effort. This occurs because increased trust lowers the minimum delivery commitment ratio, allowing the retailer to voluntarily share more supply risk in exchange for lower-cost products. This creates a mutually beneficial risk-sharing arrangement between the retailer and supplier. When extending the framework to a dual-channel setting with a reliable backup option, the retailer consistently leverages trust and risk-sharing to lower sourcing costs. Concurrently, fluctuations in trust prompt the retailer to strategically shift order allocations between channels based on the primary supplier’s maximum effort capacity. Multi-period analysis shows a positive relationship between trust and the supplier’s expected profit, with optimal maximum supply effort stabilizing under repeated cooperation. Numerical experiments demonstrate that dual-channel decentralized decision-making achieves bullwhip effect mitigation quantitatively comparable to the centralized benchmark, while also alleviating moral hazard issues and benefiting retailers. These results indicate that the proposed mechanism effectively curbs opportunistic behavior and promotes sustainable, mutually advantageous supply chain collaboration. Full article

This study examines customer retention intention in neobanking environments using a theory-informed explainable machine learning framework. Existing digital banking research typically relies on linear modelling approaches to explain retention behaviour, potentially overlooking nonlinear, value-range-dependent, and interaction-based predictive patterns. Using a publicly available survey of 305 neobank users, this study compares regularized linear models, a partial least squares structural equation modelling (PLS-SEM)-inspired benchmark, and XGBoost (version 3.2.0) under repeated nested cross-validation. SHapley Additive exPlanations (SHAP)-based explainability, SHAP interaction analysis, generalized additive model (GAM) diagnostics, construct-level aggregation, and construct-sensitivity checks are used to interpret model behaviour and assess robustness. The results show that XGBoost substantially outperforms the linear benchmarks, achieving the lowest average RMSE and highest average R² across 100 out-of-sample test-fold estimates. Trust-related indicators provide the largest share of model-based predictive importance, followed by perceived security and switching costs. SHAP and GAM diagnostics suggest that trust and switching costs may contribute to retention intention in heterogeneous and nonlinear ways, while perceived security displays a more stable positive predictive pattern. Age-related nonlinearities appear weak and should be interpreted cautiously given the young sample profile. The analysis also suggests possible non-additive relationships between trust and perceived security. The study contributes to digital banking and FinTech research by showing how explainable machine learning can complement theory-driven retention models, identify potentially nonlinear predictive patterns, and preserve interpretability. The findings offer practical insight for trust-building, visible security assurance, and retention diagnostics in neobanking contexts. Full article

The convergence of Software-Defined Networking (SDN) and Blockchain (BC) creates a symbiotic relationship in which SDN’s programmable global visibility complements BC’s decentralized, immutable trust model to address critical cybersecurity vulnerabilities and cyber attacks. Addressing the fragmentation in the current literature, this study rigorously investigates BC and SDN (B-SDN) integration with the primary objectives of: (1) differentiating impacts across varied sectors, including the Internet of Things (IoT), Smart Grids, and Vehicular Ad Hoc Networks (VANETs) and more; (2) analyzing critical performance metrics such as energy efficiency and scalability; (3) classifying mitigation, detection, and prevention schemes for specific threats; (4) examining novel Artificial Intelligence (AI) methods; and (5) identifying open challenges and future research directions. Methodologically, this study conducts a survey of state-of-the-art B-SDN studies to investigate six key areas: Industry-specific applications, security mechanisms, defense strategies, defenses against specific attacks, AI integration, and implementation performance. The findings demonstrate that B-SDN integration shows strong potential in simulated and prototype environments to mitigate specific high-impact threats, such as Distributed Denial of Service (DDoS), Man-in-the-Middle (MiTM), and spoofing, across various domains, including IoT, 5G/6G, VANETS, and Smart Grid. Despite the benefits and advantages promised by B-SDN, several limitations continue to exist, including the latency–security trade-off inherent to consensus protocols and scalability constraints in large-scale deployments. Finally, open research challenges persist in AI-driven automation, particularly in Federated Learning (FL) and in the development of standardized interoperability protocols required to enable the transition from conceptual models to operational systems. Full article

Mature technical business-to-business (B2B) markets challenge the canonical commitment–trust hierarchy because product parity, informational asymmetry, long-cycle repeat purchasing and enduring dyadic relations may decouple the antecedents of trust from those of commitment. This study re-specifies the commitment–trust model by proposing a dual-pathway architecture in which communication is associated with commitment via trust, whereas product quality and salesperson behaviour are associated with commitment through perceived value. The model was tested through a cross-sectional survey of Portuguese business customers in the paint sector (n = 101), analysed using partial least squares structural equation modelling. The results corroborate the five positive hypotheses: communication strongly predicts trust; trust is the strongest predictor of commitment; product quality and salesperson behaviour both predict perceived value; and perceived value retained a smaller but significant direct effect on commitment. The theoretically motivated non-effect of perceived value on trust is also supported, indicating that, under the specified scope conditions, trust is formed primarily through epistemic and communicational mechanisms rather than through utilitarian value aggregation. The study contributes by refining the commitment–trust tradition, distinguishing epistemic–relational and utilitarian routes to commitment, and offering managers a pathway-specific basis for allocating relational investments in mature technical B2B markets. Full article

Greenwashing in food marketing undermines consumer trust and impedes Sustainable Development Goal 12 (SDG 12). While prior research has established linkages between greenwashing perception, green skepticism, and purchase intention, no publicly deployed decision support tool has been developed for practitioner use. This study applies Design Science Research (DSR) methodology to translate validated behavioral models into a deployable decision support system rather than re-testing established relationships. We present the development, deployment, and evaluation of the Greenwashing Advertising Message Assessment (GWAMA), a web-based DSR artifact grounded in a validated Stimulus–Organism–Response (S-O-R) structural equation model. GWAMA integrates factor-loading-weighted composite scoring with SEM-derived parameters to generate real-time greenwashing risk diagnostics for food advertising messages. Usability was evaluated with 150 Thai food industry professionals using a Technology Acceptance Model (TAM) instrument applied to the live system. Results provide indicative evidence of stakeholder acceptance, with high perceived usefulness, ease of use, and intention to use. This study contributes by demonstrating how validated behavioral models can be translated into a publicly deployable decision support artifact, with practical implications for sustainable marketing governance and SDG 12 implementation in emerging economies. Full article

This study examines the influence mechanism of Chinese ethical leadership on university teachers’ salary satisfaction by constructing a moderated mediation model. We randomly collected questionnaire data from 958 university teachers in Gansu Province, China. Key results are as follows: (1) Chinese ethical leadership, trust in colleagues and leaders, salary satisfaction, and workplace mindfulness are significantly positively correlated. (2) Trust in colleagues and leaders partially mediates the relationship between Chinese ethical leadership and salary satisfaction. (3) Workplace mindfulness negatively moderates the link between ethical leadership and trust, with higher mindfulness weakening this positive effect. (4) The moderated mediation effect is significant, as the mediating effect of trust declines with increasing mindfulness. These findings uncover the unique pathway of ethical leadership in shaping faculty salary satisfaction and provide empirical evidence and practical guidance for university management optimization. Full article

This study examines how social media–driven information environments shape pro-environmental travel decision-making within the broader context of sustainable tourism and digital information expansion. It aims to explain how informational, cognitive, and evaluative mechanisms jointly influence behavioral intention by integrating perceived trustworthiness of user-generated content, ecological awareness, attitude formation, and cognitive processing bias within a moderated mediation framework. Data were collected from 315 respondents in Azerbaijan through a structured survey and analyzed using structural equation modeling to test both mediating and conditional relationships. The results show that perceived trustworthiness of user-generated content significantly strengthens attitude formation, which is the strongest predictor of behavioral intention. Trust also has a direct effect, but its influence mainly operates through evaluative pathways. Ecological awareness partially mediates the relationship between trust and intention, indicating multiple parallel mechanisms. Furthermore, cognitive processing bias weakens the effect of trust on attitude and reduces indirect effects. Overall, the findings suggest that sustainable tourism behavior is driven more by credibility-based cognitive evaluation than by mere information availability, highlighting the importance of credibility-enhancing and cognitively effective communication strategies. Full article

This study systematically explores the underlying mechanisms of collaborative innovation driving the green transformation of traditional energy enterprises. Existing research primarily focuses on enterprise scale and overall competitiveness, rarely delving into these specific collaborative pathways. Furthermore, studies employing evolutionary game theory to analyze the tripartite relationship among the government, traditional energy, and emerging technology enterprises remain fragmented, failing to fully capture the dynamic mechanisms of multi-stakeholder strategic choices. To bridge these gaps, this paper constructs a tripartite evolutionary game model incorporating coordination costs and the benefit distribution ratio to explore their influence mechanisms. Replicator dynamics equations are employed to identify stable cooperation conditions, overcoming traditional two-party framework constraints. Additionally, MATLAB R2024b numerical simulations validate the theoretical findings. The results reveal two evolutionarily stable equilibrium points. First, higher initial willingness among participants accelerates the system’s evolution toward a stable cooperative state. Second, coordination costs induced by information asymmetry act as a core bottleneck that deters participation and risks collaborative collapse. Third, targeted government incentives and a rational benefit distribution ratio directly determine cooperation willingness; notably, enterprises adopt collaborative strategies only when this ratio falls between 0.27 and 0.69. Fourth, fair and transparent supervision is crucial for mitigating trust deficits and distribution disputes. Ultimately, scientifically designing incentives, optimizing benefit structures, promoting information sharing, and establishing robust supervision effectively facilitate a sustainable tripartite collaborative innovation pattern. Full article