Search Results (1,752)

The rapid expansion of electric vehicle (EV) charging infrastructure has increased the importance of improving the user experience alongside expanding charging availability. While previous studies have primarily examined EV adoption from technological, economic, and infrastructural perspectives, limited research has investigated how Human Factors characteristics of charging systems influence users’ continuance intention. This study extends the Theory of Planned Behavior (TPB) by integrating Human Factors constructs as antecedents of behavioral beliefs associated with continuance intention toward public EV charging stations in the Philippines. A quantitative cross-sectional survey was conducted among 286 EV users in the National Capital Region, and the proposed model was evaluated using Partial Least Squares Structural Equation Modeling (PLS-SEM). Interface usability significantly influenced both attitude and perceived behavioral control, while participatory ergonomics significantly influenced subjective norm. Physical ergonomics, cognitive ergonomics, and accessibility did not significantly predict their proposed behavioral beliefs. Among the TPB constructs, perceived behavioral control and attitude significantly predicted continuance intention, whereas subjective norm was not significant. Furthermore, interface usability exhibited significant indirect effects on continuance intention through both perceived behavioral control and attitude. The findings demonstrate that Human Factors characteristics contribute selectively to the behavioral mechanisms underlying continued charging-station use, with perceived behavioral control emerging as an important pathway linking the charging experience with continuance intention. The study extends TPB by positioning Human Factors as antecedents of behavioral beliefs in a post-adoption context and highlights the importance of usable, understandable, and manageable charging interactions in supporting continued engagement with public EV charging infrastructure. Full article

Background/Objectives: The transition toward healthier and more sustainable diets has increased the need for reformulated bakery and confectionery products formulated with alternative ingredients. However, validated instruments for assessing consumer acceptance of these products remain limited. This study aimed to develop and psychometrically validate a multidimensional assessment framework integrating food choice motives, green (environmental) values, health consciousness, perceived nutritional value, willingness to pay a premium, and purchase intention. Methods: A cross-sectional survey was conducted among 504 consumers in Romania using an online questionnaire. The instrument was developed by adapting established scales and by developing a new Perceived Nutritional Value scale. Dimensionality was evaluated using exploratory (EFA) and confirmatory (CFA) factor analyses. Temporal stability was assessed in an independent test–retest subsample (n = 30; 14-day interval), and the proposed conceptual model was evaluated using Partial Least Squares Structural Equation Modeling (PLS-SEM) with 5000 bootstrap resamples. Robustness was examined through a sensitivity analysis excluding respondents younger than 18 years (N = 441). Results: EFA (KMO = 0.933) and CFA (CFI = 0.965, TLI = 0.959, RMSEA = 0.061, SRMR = 0.033) supported the proposed six-factor structure. All constructs demonstrated excellent internal consistency (Cronbach’s α: 0.898–0.938), convergent validity (AVE: 0.790–0.889), discriminant validity (HTMT < 0.77), and good-to-excellent test–retest reliability (ICC: 0.82–0.91). Perceived nutritional value was positively and significantly associated with both willingness to pay and purchase intention, and willingness to pay partially mediated the association between perceived nutritional value and purchase intention. The structural model explained 46.1% of the variance in purchase intention; all hypothesized relationships were supported, and the findings remained stable in the sensitivity analysis. Conclusions: The proposed framework demonstrated good psychometric performance and provides a theory-informed measurement framework for assessing consumer acceptance of reformulated bakery and confectionery products. It may support future nutrition research, consumer studies, and the evaluation of food reformulation strategies aimed at promoting healthier and more sustainable dietary choices. Full article

The rapid adoption of Generative Artificial Intelligence (GenAI) is transforming higher education by reshaping learning experiences, student engagement, and creativity. However, little is known about the mechanisms through which GenAI enhances creativity, particularly within tourism and hospitality education. Unlike prior studies that primarily examine students’ intention to adopt GenAI, this study explains how GenAI adoption translates into creativity through enhanced learning and learning engagement while accounting for ethical risks. Drawing upon contemporary learning and creativity literature, this study examined how students’ adoption of GenAI influences creativity through the mediating roles of enhanced learning and learning engagement, while also investigating the moderating effect of perceived ethical risks associated with GenAI use. Data were collected from 420 students enrolled in tourism and hospitality faculties and institutes across Egypt. The proposed research model was tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that enhanced learning and learning engagement are the principal mechanisms through which GenAI adoption improves students’ creativity, whereas perceived ethical risks significantly weaken these positive relationships. This study contributed to the emerging GenAI literature by moving beyond technology adoption perspectives to explain how GenAI shapes creativity outcomes in higher education. It further extends tourism and hospitality education research by providing one of the first empirical examinations of the mechanisms through which GenAI enhances student creativity while accounting for ethical concerns. The findings provide practical guidance for higher education institutions seeking to integrate GenAI responsibly while fostering creativity, engagement, and innovative learning environments. Full article

This research investigates the relationships between climate change, biodiversity and nature-based tourism in the Danube Delta Biosphere Reserve (DDBR), integrating the behavioural perspective of Generation Z into an adaptive management framework. This study uses a mixed methodological approach, combining time series analysis of the period 2000–2025 with behavioural modelling, based on the primary data study. The analysis of this study includes indicators for the four complementary dimensions, namely: the climate dimension, the biodiversity dimension, the tourism activity dimension, and the behavioural dimension. The relationships among climate variables, biodiversity and tourism are investigated using AutoRegressive Distributed Lag (ARDL) models, while the behavioural component is analysed using the Partial Least Squares Structural Equation Modelling (PLS-SEM) method, applied to a sample of 419 respondents. The results highlight the existence of relationships among climate change, biodiversity and tourist activity, confirming the role of biodiversity as a central element of the attractiveness of nature-based tourism. At the same time, concern for biodiversity significantly influences the intention to visit natural destinations among Generation Z people. Therefore, our research contributes to the literature regarding socio-ecological systems and provides recommendations for the development of adaptive management aimed at biodiversity conservation and strengthening the resilience of sustainable tourism in the Danube Delta. Full article

Small- and medium-sized enterprises (SMEs) increasingly use artificial intelligence (AI)-based customer tools and social media marketing to compete in digital markets. However, prior research has not fully explained how customer-facing digital interaction and strategic customer sensing are converted into internal organisational capabilities or how alternative combinations of capabilities lead to business sustainability. In this study, we develop and test a sequential mixed-method framework for Thai SMEs. In Phase I, we applied the Interval Type-2 Fuzzy Delphi Method (IT2FDM) with 21 experts to validate 43 observed variables. In Phase II, we analysed 659 Thai SME responses using Partial Least Squares Structural Equation Modelling (PLS-SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA). The PLS-SEM measurement assessment showed that service innovation and internal learning formed a consolidated service innovation–internal learning capability (SILC) construct, with 42 indicators retained in the final measurement model. The structural model supported all hypothesised paths: AI chatbot usage, social media marketing, and customer value anticipation were positively associated with SILC; SILC was positively associated with external learning, business performance, and business sustainability; external learning was positively associated with business performance; and business performance was positively associated with business sustainability. The fsQCA results showed that no single present or absent/low condition was necessary for business sustainability and identified three sufficient pathways, with SILC and business performance present across all primary configurations. One pathway further showed that strong SILC, external learning, and business performance could support business sustainability even when AI chatbot usage, social media marketing, and customer value anticipation were weak or absent. The findings advance SME digital transformation and sustainability research by demonstrating capability conversion, integrated innovation–learning transformation, and multiple compensatory pathways to business sustainability. Full article

Background: Healthcare access in Vietnam confronts regional disparities and rising demand, requiring collaborative policies and strong workforce performance to guarantee effective and affordable services. This study scrutinises how organisational culture shapes healthcare workforce performance within Vietnam’s public healthcare organisations, with particular emphasis on organisational commitment, knowledge-sharing behaviour, and digital health transformation. Methods: This study employed a quantitative, cross-sectional survey design. Data were collected from 450 healthcare professionals in public healthcare facilities in southern Vietnam through convenience and snowball sampling, using a structured questionnaire measuring organisational culture (Denison model), organisational commitment, knowledge-sharing behaviour, digital health transformation and job performance on a six-point Likert scale. Data were analysed using partial least squares structural equation modelling (PLS-SEM) in SmartPLS 3.0. Results: The findings indicate that organisational culture is directly and substantively associated with healthcare workforce performance. In addition, knowledge sharing and digital health transformation operate as mediating mechanisms, with knowledge sharing showing a notably stronger indirect association. Notably, the relationship between organisational commitment and healthcare workforce performance was indicated to be not statistically significant. Conclusions: This study offers important practical and healthcare policy implications for healthcare administrators, human resource practitioners, public-sector leaders, and health policy stakeholders, predominantly in designing and employing targeted, culture-driven interventions aimed at improving healthcare workforce performance. Specifically, fostering a culture that encourages knowledge exchange and supports digital health transformation emerges as a critical pathway for organisational advancement. Such initiatives are instrumental in nurturing a motivated, engaged, and high-performing workforce, thereby underlining the sustainable development of public healthcare organisations. Full article

Innovation is an everyday imperative in the information and communication technology (ICT) sector, yet the psychological conditions through which well-being is associated with innovative action remain insufficiently understood. This study investigates whether subjective vitality and creative self-efficacy constitute distinct psychological pathways—an energy-based and a belief-based mechanism, respectively—through which psychological well-being becomes associated with innovative work behavior, thereby providing a more differentiated examination of the assumption that psychologically healthy employees are more likely to behave innovatively. An online survey was administered to 463 ICT-sector employees in Türkiye, and partial least squares structural equation modeling (PLS-SEM) was used to test direct and indirect relationships with comprehensive assessment of measurement quality, predictive relevance, and effect sizes. Creative self-efficacy emerged as a meaningful indirect pathway linking psychological well-being to innovative work behavior, whereas subjective vitality, though strongly predicted by well-being, showed no significant relationship with innovative outcomes. These findings suggest that not all positive psychological states are equally innovation-relevant: among ICT employees, the indirect association between well-being and innovation was evident through employees’ confidence in their own creative capability rather than through feelings of psychological energy—a distinction with meaningful implications for both theory and practice in knowledge-intensive, digitally dynamic organizations. Full article

The participating municipality plays a central role in coordinating strategic planning, resource allocation, stakeholder engagement, monitoring, and digital governance to promote sustainable tourism development. However, limited empirical evidence exists on how these governance functions collectively operate as an integrated institutional capability. This study proposed and empirically assessed Institutional Strategic Planning Capability (ISPC) as a higher-order governance construct and examined its relationships with Collaborative Governance, Smart Destination Readiness, and Perceived Sustainable Tourism Development Performance in the Provincial Municipality Daniel Alcides Carrión, Peru. The conceptual framework was developed by integrating Dynamic Capabilities Theory, Stakeholder Theory, and the municipal tourism governance literature. A quantitative, explanatory, cross-sectional research design was employed using questionnaire data collected from 120 municipal employees involved in planning, finance, tourism, infrastructure, environmental management, and administration. The proposed framework was evaluated using Partial Least Squares Structural Equation Modeling (PLS-SEM) with 5000 bootstrap resamples. The higher-order ISPC construct was empirically assessed through indicator reliability, internal consistency, convergent validity, discriminant validity, and higher-order construct assessment before evaluating the structural relationships, explanatory capability, and predictive performance of the model. The results demonstrate satisfactory initial measurement evidence across all constructs. ISPC exhibited significant positive relationships with Collaborative Governance and Smart Destination Readiness, while both governance mechanisms were positively associated with Perceived Sustainable Tourism Development Performance. The structural model demonstrated satisfactory explanatory power and predictive capability within the study context. The findings should be interpreted within the limitations of a cross-sectional, perception-based study conducted in a single municipality. The study contributes conceptually by proposing ISPC as an integrated higher-order governance construct and provides context-specific empirical evidence supporting evidence-based municipal tourism planning in the Peruvian context. Full article

Soil quality constitutes a fundamental foundation for maintaining soil productivity, ecological function and crop health. However, existing research on soil quality assessment and its limiting factors in Trichosanthes kirilowii Maxim. planting areas remains insufficient. To construct a soil quality assessment system suitable for T. kirilowii Maxim. planting areas and identify key limiting factors, this study took 46 sampling sites from three typical T. kirilowii production areas in northwestern Hubei, the Jianghan Plain and southeastern Hubei Province as research objects. Thirteen physicochemical soil indicators were measured. Principal component analysis (PCA) combined with the Norm value was used to derive the minimum data set (MDS). Three scoring functions were compared to evaluate their applicability for soil quality assessment. The obstacle degree model was applied to identify the main limiting factors of soil quality, and partial least squares structural equation modeling (PLS-SEM) was used to explore the potential relationships associated with soil quality variation. The results show that an MDS composed of soil organic matter (SOM), alkali-hydrolyzable nitrogen (AN), bulk density (BD), electrical conductivity (EC) and total phosphorus (TP) can effectively characterize soil quality. Compared with linear standardization and membership function standardization, the non-linear function (SNL) standardization method performs the best (E_f = 0.78, E_R = 0.05), and a soil quality index (SQI) calculated based on the MDS and total data set (TDS) shows a significant positive correlation (R² = 0.851, p < 0.001). The average SQI of T. kirilowii planting areas in Hubei Province is 0.49, which is a medium level, and shows obvious spatial differences among different regions, in the order of northwestern Hubei (0.59) > southeastern Hubei (0.49) > Jianghan Plain (0.39). Obstacle degree analysis shows that organic matter and alkali-hydrolyzable nitrogen are the main limiting factors affecting soil quality, but there are obvious differences among regions. PLS-SEM analysis indicated that soil fertility-related factors were positively associated with SQI (path coefficient = 0.720, p < 0.001), whereas the soil’s physical and salinity-related factors showed negative associations with SQI (path coefficient = −0.259, p < 0.05). Altitude showed indirect associations with SQI through its relationships with soil properties, with a total effect of 0.480, and the model explained 85.7% of the variation in SQI. This study confirms that the constructed MDS performs comparably to the TDS in the present dataset for soil quality assessment in T. kirilowii planting areas in Hubei Province. Insufficient organic matter and alkali-hydrolyzable nitrogen were identified as the main factors limiting soil quality, suggesting that improving organic matter accumulation and nitrogen availability should be prioritized in soil management in T. kirilowii planting areas. This study can provide a theoretical basis for soil quality assessment, precise fertilization and sustainable soil development in T. kirilowii planting areas. Full article

Project management plays a critical role in ensuring project success and organizational competitiveness, particularly in Saudi Arabia’s rapidly evolving construction sector. Artificial intelligence (AI) has emerged as a transformative technology with the potential to improve project performance through enhanced operational processes and managerial decision-making. This study examines the impact of AI integration on construction project outcomes (PO), with operational efficiency (OE) and managerial decision-making (MDM) acting as mediating variables. A quantitative research approach was adopted, and data were collected from 216 professionals working in Saudi Arabia’s private construction sector. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings supported all proposed hypotheses, demonstrating that AI integration has a significant positive effect on PO. Furthermore, OE and MDM were found to significantly mediate the relationship between AI integration and PO. The structural model explained 65% of the variance in PO, indicating substantial explanatory power. The findings contribute to the growing body of knowledge on AI adoption in construction project management and provide practical insights for organizations seeking to enhance PO through AI-driven digital transformation initiatives in support of Saudi Vision 2030. Full article

AI-generated reviews have become a core tool for hotel booking platforms in assisting user decision-making, yet existing research has not systematically explored the emotional tendencies of GAI reviews or the potential mechanisms by which temporal disclosure influences user decisions. This study integrates the Information Adoption Model (IAM) and the Elaboration Likelihood Model (ELM), incorporates the affordance perspective of GAI, employs a 2 × 2 experimental design (temporal disclosure × review valence), analyzes sample data from 649 travelers, and conducts empirical analysis using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results demonstrate that temporal disclosure significantly enhances cognitive involvement; the effect of review valence on cognitive involvement is moderated by GAI affordance—high GAI affordance mitigates the inhibitory impact of positive reviews on cognitive involvement; empathy toward GAI information does not directly reduce psychological distance to hotels but operates indirectly through full mediation via psychological distance to GAI; psychological distance to GAI also indirectly influences booking intent via full mediation through psychological distance to the hotel. This study elucidates the mechanisms linking the emotional characteristics of AI-generated reviews with the impact of temporal disclosure on traveler decision-making, supplements theoretical frameworks for consumer decision-making in AI contexts, expands the IAM for AI applications, and provides empirical evidence and practical recommendations for optimizing GAI review presentation strategies on booking platforms. Full article

Background/Objectives: Family dietary imbalance is an important source of the double burden of malnutrition, and dietary arrangements in multigenerational households are often deeply embedded in intergenerational caregiving relationships. However, the cognitive formation mechanism through which dietary caregiving behaviors driven by care and responsibility may instead lead to dietary imbalance still lacks systematic explanation. Therefore, this study aimed to examine the cognitive formation mechanism of dietary imbalance behaviors in Chinese multigenerational households. Methods: This study takes primary dietary caregivers in Chinese three-generation households as the research subjects. It integrates the false consensus effect, cognitive dissonance theory, and the information–motivation–behavioral skills (IMB) model. Based on 467 valid samples, the study conducts empirical analysis using partial least squares structural equation modeling (PLS-SEM) and importance-performance map analysis (IPMA). Results: The results show that caregivers’ subjective judgments about family members’ dietary needs based on their own experience trigger cognitive dissonance and further promote their re-examination of dietary risk information, caregiving responsibilities, and family normative expectations. Among these factors, caregiving responsibilities and subjective norms are key factors in improving dietary regulation self-efficacy, whereas the effect of risk information perception on self-efficacy is not significant. The IPMA results further show that self-efficacy is the most important factor driving the formation of behavioral intention to regulate healthy family diets. Conclusions: This study reveals the psychological mechanism through which dietary imbalance behavior in multigenerational households moves from subjective need judgment to the formation of future regulation intention. It extends the application of the IMB model in family caregiving contexts and provides a theoretical basis and practical implications for the formulation of family health promotion and dietary intervention strategies. Full article

Renewable energy communities (RECs) are increasingly recognised as important instruments for accelerating the transition towards decentralised, low-carbon energy systems. However, technological progress and supportive policies alone cannot ensure their success, as participation depends largely on citizens’ behavioural readiness. This study investigates the behavioural determinants of participation in renewable energy communities by extending the Theory of Planned Behaviour (TPB) with four motivational dimensions: environmental, economic, technical, and social. A quantitative cross-sectional survey of 174 household electricity users in Slovenia was analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings show that environmental and economic motivations were positively associated with Attitudes, Technical Motivation was positively associated with Perceived Behavioural Control, and Social Motivation was positively associated with Subjective Norms. These TPB constructs are positively associated with behavioural readiness to participate in renewable energy communities. A supplementary exploratory multi-group analysis suggested possible differences between prosumers and conventional consumers. Prosumer status reflected individual household renewable electricity production and not verified REC membership, while Behavioural Readiness captured prospective stated intention and willingness rather than observed participation. However, because the prosumer subgroup comprised only 15 respondents, these group-specific patterns should be interpreted cautiously and require confirmation in larger and more balanced samples. The study extends the Theory of Planned Behaviour by integrating a multidimensional motivational framework and conceptualises participation in renewable energy communities as a socio-technical behavioural process. The findings provide empirically informed insights for policymakers, municipalities, and renewable energy community developers seeking to support citizens’ behavioural readiness to participate in renewable energy communities. Full article

Rapid urbanization in China has intensified ecological degradation, loss of architectural and cultural heritage, and declining well-being in traditional villages. Existing conservation approaches often address ecological, economic, or physical heritage issues in isolation, while insufficiently incorporating residents’ quality of life (QoL) as a central criterion of sustainability. This study develops a human-centred traditional village preservation framework grounded in the ecovillage concept and a QoL-oriented sustainability paradigm, using Langde Miao Village in Guizhou Province as a representative ethnic heritage settlement. A mixed-methods approach combining systematic literature review, Delphi expert consultation, household surveys, and partial least squares structural equation modelling (PLS-SEM) was employed to examine the interrelationships among ecological, cultural, social, and economic dimensions of sustainable built heritage. Based on valid responses, the empirical results indicate that the ecological dimension exerts the strongest direct effect on residents’ quality of life, followed by the cultural and economic dimensions, while the social dimension shows a comparatively weaker effect. The proposed framework provides a community-centred model for sustainable architectural heritage conservation and rural revitalization in traditional villages. Full article

Artificial intelligence (AI)-powered online shopping is profoundly reshaping the way in which consumers engage with sustainable clothing. However, the relationships between digital multisensory cues and perceived quality with sustainable consumption intention still need to be explored. Based on the Stimulus–Organism–Response (S-O-R) framework, the present study explores the relationships of digital multisensory cues and perceived quality with consumers’ flow experience, pleasure, and responses (e.g., engagement, loyalty, and sustainable consumption intention) in the context of AI-powered online shopping using a cross-sectional, scenario-based, assisted recall survey. A total of 571 valid responses were retained for analysis. Partial least squares structural equation modelling (PLS-SEM) was adopted for data analysis. The findings indicate that digital multisensory cues showed a positive relationship with pleasure, whereas perceived quality was positively associated with both flow experience and pleasure. Flow experience was positively linked to pleasure, which was further associated with engagement and sustainable consumption intention. Statistically significant indirect effects on sustainable consumption intention through pleasure were observed for flow experience, digital multisensory cues, and perceived quality. The results of this study offer practical implications for retailers seeking to design emotionally engaging AI-powered shopping experiences that may support sustainable consumption intention. Full article