Search Results (277)

Using the “Cloud Tour Dunhuang” digital museum as a case, this study integrates an enhanced TAM3 with UTAUT and introduces two external variables—cultural identity and technological innovation—to construct a comprehensive framework for users’ continuance intention. Based on 484 valid responses, we employ a sequential mixed-method design combining structural equation modeling (SEM), artificial neural networks (ANNs), necessary condition analysis (NCA), and grounded theory (GT). The results show that (1) cultural identity and technological innovation significantly promote behavioral intention and continuance behavior by strengthening perceived usefulness; (2) performance expectancy and social influence exert significant effects, whereas effort expectancy and facilitating conditions are comparatively weaker; and (3) the integrated model delivers superior explanatory power and predictive performance relative to single-path baselines. This research enriches user-behavior scholarship in digital cultural heritage and offers theory-informed, practical guidance for improving user retention and optimizing platform design. Full article

This study investigates the role of family involvement and succession planning in shaping the long-term sustainability of family businesses in Indonesia, with a specific focus on the mediating effect of transgenerational entrepreneurial orientation (TEO). This research responds to calls for integrative models that move beyond examining these factors in isolation. Indonesia offers a unique context due to its dominance of family-controlled firms and informal succession traditions, which shape entrepreneurial value transmission across generations. A quantitative approach was employed using survey data from 210 respondents representing active family businesses in Indonesia. Partial least squares structural equation modeling (PLS-SEM) with SmartPLS 4.0 was used to test reliability, validity, and structural relationships. Additional analyses included HTMT for discriminant validity, CVPAT for predictive relevance, and importance–performance map analysis (IPMA) to identify managerial priorities. The results reveal that family involvement and succession planning both exert significant positive effects on long-term family business sustainability, with TEO playing a mediating role. Family involvement strongly enhances both sustainability and entrepreneurial orientation, while succession planning contributes more indirectly through the development of TEO. The IPMA indicates that family leadership in governance and openness to innovation are highly important but underperforming drivers, suggesting key areas for improvement. The model explains 51.9% of the variance in TEO and 48.6% in long-term sustainability, with significant mediation paths (β = 0.092–0.104, p < 0.05). The cross-sectional design limits causal inference, and the focus on Indonesian firms may constrain generalizability to other cultural contexts. Future research could adopt longitudinal and cross-country comparative designs while also examining the role of digital transformation and generational differences in sustaining family firms. The findings highlight the need for Indonesian family firms to professionalize succession planning while strengthening transgenerational entrepreneurial orientation. Practical steps include formal mentoring, clear successor criteria, and embedding innovation and proactiveness in family governance. This study extends the family business literature by conceptualizing TEO as a dynamic capability that bridges family involvement, succession planning, and sustainability. By integrating these perspectives, it offers a more comprehensive understanding of how family firms can achieve resilience and continuity across generations. Full article

The long-term monoculture of Eucalyptus plantations in southern China has raised ecological concerns, prompting a shift towards mixed-species plantations as a sustainable alternative. This study investigates the mechanisms by which companion tree species enhance soil functionality in subtropical red soil regions. A field experiment compared a pure Eucalyptus (CK) plantation with three mixed-species plantations: Eucalyptus × Mytilaria laosensis (A × M), Eucalyptus × Magnolia hypolampra (A × H), and Eucalyptus × Michelia gioii (A × X). Comprehensive soil analyses were conducted at three soil depths (0–20 cm, 20–40 cm, and 40–60 cm) to assess chemical properties, enzyme activities, and humus components, and soil organic carbon (SOC) molecular structure was characterized by Fourier-Transform Infrared Spectroscopy (FTIR), with the relationships quantified using structural equation modeling (SEM) to test predefined causal hypotheses. The results showed that A × H significantly boosted topsoil fertility (e.g., OM: 46.61 g/kg), while A × M enhanced the recalcitrant organic carbon (ROC: 35.29 g/kg), indicating superior carbon sequestration potential. The FTIR analysis revealed species-specific alterations in SOC chemistry, such as increased aromatic compounds in A × H/A × X. The SEM analysis demonstrated that the latent variable “Humus” (reflected by LOC and ROC) directly and positively influenced the latent variable “Soil Fertility” (reflected by pH, OM, and AP; path coefficient: 0.62). In contrast, the latent variable “Organic Components” (reflected by specific FTIR functional groups) exhibited a significant direct negative effect on “Soil Fertility” (−0.41). The significant pathway from “Organic Components” to “Enzymatic Activity” (0.55*) underscored the role of microbial mediation. The study concludes that mixed plantations, particularly with Mytilaria laosensis (A × M), improve soil health through an “organic input–microbial enzyme response–humus formation” pathway, offering a scientific basis for sustainable forestry practices that balance productivity and ecological resilience. Full article

As education undergoes digital transformation, ChatGPT-4 has emerged as one of the most visible tools of generative artificial intelligence. While widely discussed, its impact on student satisfaction and learning outcomes in higher education remains underexplored. This study investigates the factors that shape art and design students’ satisfaction when using ChatGPT to support coursework. Unlike previous research focusing on ChatGPT adoption behavior, this study extends the Information Systems Success Model (ISSM) to the context of art and design education. Drawing on 435 valid survey responses, we employed a mixed-methods approach. Partial Least Squares Structural Equation Modeling (PLS-SEM) was first applied to examine how system quality, compatibility, personal innovativeness, and perceived usefulness influence satisfaction directly and through mediating mechanisms. To complement this, fuzzy-set Qualitative Comparative Analysis (fsQCA) was used to identify multiple combinations of conditions that lead to high satisfaction. The findings show that compatibility, perceived usefulness, and personal innovativeness significantly enhance satisfaction, with path coefficients of 0.378, 0.342, and 0.155, respectively. Importance–Performance Map Analysis (IPMA) further highlights personal innovativeness and system quality as critical drivers. By providing both theoretical and practical insights, this study contributes to the growing body of research on generative AI in art and design education and informs the design of courses and digital learning tools. Full article

“GenAI” assistants are gradually being integrated into daily tasks and learning, but their uptake is no less contingent on perceptions of credibility or safety than on their capabilities per se. The current study hypothesizes and tests its proposed two-road construct consisting of two interface-level constructs, namely perceived transparency (PT) and perceived safety/guardrails (PSG), influencing “behavioral intention” (BI) both directly and indirectly, via the two socio-cognitive mediators trust in automation (TR) and psychological reactance (RE). Furthermore, we also provide formulations for the evaluative lenses, namely perceived usefulness (PU) and “perceived risk” (PR). Employing survey data with a sample of 365 responses and partial least squares structural equation modeling (PLS-SEM) with bootstrap techniques in SMART-PLS 4, we discovered that PT is the most influential factor in BI, supported by TR, with some contributions from PSG/PU, but none from PR/RE. Mediation testing revealed significant partial mediations, with PT only exhibiting indirect-only mediated relationships via TR, while the other variables are nonsignificant via reactance-driven paths. To uncover non-linearity and non-compensation, a Stage 2 multilayer perceptron was implemented, confirming the SEM ranking, complimented by an importance of variables and sensitivity analysis. In practical terms, the study’s findings support the primacy of explanatory clarity and the importance of clear rules that are rigorously obligatory, with usefulness subordinated to credibility once the latter is achieved. The integration of SEM and ANN improves explanation and prediction, providing valuable insights for policy, managerial, or educational decision-makers about the implementation of GenAI. Full article

Corncob residues, an abundant but underutilized organic resource in Northeast Asia, offer substantial potential for improving soil health and plant productivity. This study investigates the effects of corncob returning on soil physicochemical properties, microbial processes, and the performance of Eleutherococcus sessiliflorus in a cold–temperate region (Jilin Province, China). The treatments included no-amendment control (CK), corncob incorporation (CI), and corncob mulching (CM). Corncob returning significantly increased soil organic carbon, moisture content, and the availability of N–P–K, while reducing soil bulk density, thus improving soil structure and nutrient availability. Both CI and CM treatments enhanced microbial biomass C, N, and P, as well as nutrient-cycling enzyme activities (β-glucosidase, urease, and alkaline phosphatase), accelerating C–N–P turnover in the rhizosphere. These improvements resulted in enhanced plant nutrient status and significant gains in biomass, with plant height and fruit number increasing by up to 44% and 136%, respectively. Multivariate analysis and PLS-SEM revealed that soil improvements strongly stimulated enzyme activity (path coefficient = 0.956), and enhances the microbial niche, thereby promoting plant traits through nutrient release (enzyme → plant path coefficient = 0.694). Microbial functional activity, rather than microbial richness, plays a more crucial role in plant growth promotion. Collectively, these findings underscore that corncob returning improves E. sessiliflorus performance through a soil biochemical activation pathway mediated by microbial metabolism and enzymatic nutrient release. This study provides strong evidence supporting corncob recycling as a cost-effective, environmentally sustainable approach for improving medicinal plant production and advancing circular agriculture in cold-region ecosystems. Full article

This study explores the complex psychological mechanisms linking career adaptability to work engagement under AI-driven workplaces. We examine the mediating role of job satisfaction and investigate a key hypothesis: that the adaptive benefits of AI self-efficacy are dampened by the emotional costs associated with AI anxiety. A dual-analytical approach was employed on a sample of 311 young Chinese workers. First, we conducted conditional process analysis using PROCESS Model 11 with 5000 bootstrapped samples to test for conditional indirect effects. Second, we utilized latent variable structural equation modeling for robust validation at the structural level. Analyses were adjusted for demographic and occupational covariates. As a result, the initial PROCESS analysis revealed that the key triple interaction (career adaptability × AI self-efficacy × AI anxiety) was statistically significant in all three test models (e.g., Model 1: b = −0.3509, p = 0.0075). Further analysis showed that the positive moderating effect of AI self-efficacy was contingent on AI anxiety; it was strongest at low AI anxiety and weakest (but still significant) at high AI anxiety. However, the more robust latent variable SEM (CMIN/DF = 1.569, CFI = 0.939, RMSEA = 0.043) revealed a critical separation of effects. The indirect effect operates exclusively through intrinsic job satisfaction, which was significantly predicted by the unified second-order career adaptability factor (b = 1.361, BCa 95% CI [1.023, 1.967]). The path from extrinsic satisfaction to WE was non-significant (b = 0.107, BCa 95% CI [−0.030, 0.250]). Furthermore, the SEM isolated a significant direct positive effect from the unified career adaptability factor to work engagement (b = 0.715, BCa 95% CI [0.385, 1.396]). This study highlights that the adaptability–engagement link operates via two distinct mechanisms: an indirect pathway from a unified career adaptability construct through intrinsic job satisfaction, and a direct pathway from career adaptability to work engagement. While PROCESS analysis suggests that anxiety dampens confidence, our SEM results clarify that this should be interpreted cautiously, as the mediation pathway via extrinsic satisfaction is not robust to measurement error. These findings underscore a multi-faceted mandate for organizations: leaders must not only manage AI anxiety but also foster holistic career adaptability to enhance intrinsic job quality and build direct engagement. Full article

The article’s main focus is on identifying the key enablers that are making Industry 4.0 adoption easier, utilizing structural equation modeling via SPSS version 26. A comprehensive examination of previous studies led to the identification of 10 main enablers and 35 associated sub-enablers. Data collected from 182 manufacturing companies in India, selected by simple random sampling, was used for quantitative research. The analysis basically depends on PLS-SEM and CB-SEM (Partial Least Squares and Covariance-Based Structural Equation Modeling) path modeling. The findings indicate that technological enablers such as data analytics and artificial intelligence, computational power and connectivity, technologies that integrate physical and digital systems, and other enabling technologies are crucial to Industry 4.0 adoption. Additionally, organizational enablers (including a supportive organization, government efforts and promotions, and human resources) are also found to be significant contributors to Industry 4.0 implementation. Additionally, the study identified a significant mediating effect between technological and organizational enablers, emphasizing the importance of collaborative visualization mechanisms, established through bootstrapping with bias-corrected confidence intervals. Strengthening technological, organizational, and collaborative capabilities through Industry 4.0 adoption allows firms to attain improved operational performance while advancing sustainability objectives. These results contribute to the present understanding of Industry 4.0 adoption by offering useful implications for policymakers and industry practitioners. These insights guide managers and policymakers in structuring digital transformation initiatives. Full article

As a vital component of urban transportation systems, subways play a crucial role in the development of a city. However, opportunistic behaviors by subway construction contractors frequently occur, adversely affecting project objectives. This study employs literature review methods to identify six key dimensions that influence the governance of opportunistic behaviors by subway project contractors, thereby constructing a theoretical model of governance factors. Based on this theoretical framework, hypothesis testing and questionnaire design were conducted. Structural Equation Modeling (SEM) path analysis identified construction process management as the direct cause influencing the governance of opportunistic behavior by subway project contractors, exerting a direct effect on such governance. Meanwhile, industry standardization, external oversight mechanisms, project governance quality, contractor credit evaluation, and internal organizational controls within the construction firm were identified as indirect governance factors. A system dynamics model was employed for dynamic simulation analysis of the governance system, revealing the dynamic evolution of opportunistic behavior governance levels under various influencing factors. Scenario simulations identified the pathway, industry standardization → internal controls within the construction organization → project governance quality → construction process management → opportunistic behavior governance, as yielding the lowest frequency of opportunistic behavior occurrence and optimal governance levels. The findings provide a governance basis for addressing the frequent occurrence of opportunistic behavior in subway construction projects. Full article

Homework is a key learning activity that promotes students’ self-regulation, motivation, and academic achievement. Previous studies highlight the importance of parental and teacher autonomy support in fostering these outcomes, but the mechanisms underlying these relationships require further investigation. This study investigates the effects of parental and teacher autonomy support on students’ self-regulation skills, mathematics homework completion, and academic achievement. Additionally, it examines whether gender moderates these relationships. The research was conducted with 530 middle school students from five public schools in Istanbul, covering 5th, 6th, and 7th grades. Data were collected on teachers’ and parents’ autonomy support in homework, students’ self-regulation strategies, homework behaviors, and academic performance. Analyses were performed using SPSS 25 and AMOS 25 software, employing structural equation modeling (SEM) with mediation paths, multi-group path analysis, and correlation tests. The results indicate that both parental and teacher autonomy support positively influence students’ use of self-regulation strategies, which in turn enhances homework completion and academic success. Self-regulation was found to mediate these relationships, confirming its crucial role in academic outcomes. However, gender did not significantly moderate these associations. This study advances the understanding of how parental and teacher autonomy support influence self-regulation, homework behavior, and academic achievement, contributing to the existing literature. By examining the mediating role of self-regulation and the moderating effect of gender, it provides in-depth insights into variations in homework engagement and academic outcomes. Findings highlight the importance of autonomy-supportive practices by parents and teachers to foster students’ independent study skills. Future studies could extend these findings by examining subject-specific differences and longitudinal effect. Full article

This study examines the mechanisms through which ecological public art influences pro-environmental behavior, addressing the urgent challenges of the global ecological crisis and sustainable urban development. Using the 5th Shanghai Urban Space Art Season (SUSAS) as a case study, a serial multiple mediation model was established, with ecological public art perception as the independent variable, environmental psychological ownership and ecological awareness as mediators, and pro-environmental behavior as the dependent variable. Based on 326 valid responses, structural equation modeling (SEM), which integrates confirmatory factor analysis (CFA) and path analysis, demonstrates that ecological public art perception significantly enhances pro-environmental behavior. Environmental psychological ownership and ecological awareness function not only as independent mediators but also jointly constitute a serial mediation pathway. The findings reveal a multidimensional process whereby ecological public art enhances pro-environmental behavior through “perceptual activation–emotional identification–cognitive enhancement–behavioral transformation”. Building on these insights, the study proposes intervention strategies focusing on multi-sensory integration, emotional narrative, digital technology application, and community-based practices to reinforce the role of ecological public art in urban environmental governance and sustainable development. Overall, this research advances the theoretical understanding of the social functions of public art and offers a valuable perspective for fostering ecological awareness and action. Full article

Against the backdrop of sustainability, open innovation has been widely adopted by various businesses. Within scholarly communities, how corporate openness affects innovation performance has also become a focal topic. Nevertheless, existing literature has not carried out an in-depth exploration of the intrinsic mechanisms that link openness to open innovation performance. To illustrate how corporate openness affects open innovation performance, this research intends to incorporate knowledge management capability and organizational learning as dual mediating variables. This study utilizes several research methods, including SEM analysis and Bootstrap testing, to confirm the relevant hypotheses. The findings reveal that openness and open innovation performance are mediated by external and internal knowledge management capability. In the same vein, the relationship between the two is also mediated by explorative learning and exploitative learning. Furthermore, two dual-chain mediating paths enable openness to improve open innovation performance, namely “external knowledge management capability—explorative learning” and “internal knowledge management capability—exploitative learning”. By establishing a chain mediation mechanism of “capability-learning-performance”, this study delivers a more holistic theoretical structure for deciphering the mechanisms that shape open innovation performance, in turn propelling theoretical advancements within this domain. Full article

To optimize the microstructure and mechanical properties of Ti6Al4V alloys fabricated via Selective Laser Melting (SLM), this study proposes an optimization approach based on the chessboard scanning strategy. A systematic comparison of three scanning strategies—alternating, stripe, and chessboard scanning—was conducted to examine their effects on thermal input distribution, grain refinement, phase composition, and mechanical performance. Characterization results from Scanning Electron Microscopy (SEM), Electron Backscatter Diffraction (EBSD), and Transmission Electron Microscopy (TEM) revealed that the chessboard scanning strategy effectively refines the grain size to 88.64 ± 10.79 μm and increases the strengthening phase α′ content to 53.3%. Mechanical testing showed a tensile strength of 1179 ± 17 MPa (11.02% higher than stripe scanning) and elongation of 7.9 ± 0.4%. This strategy promotes random grain orientation by altering the scanning path, disrupting directional solidification, and suppressing texture formation. Microstructural mechanism analysis suggests that dislocation strengthening, increased α′ content, and grain refinement synergistically enhance both strength and ductility. These findings provide theoretical support for optimizing SLM parameters and the design of Ti6Al4V alloys’ microstructure and mechanical properties. Full article

Against the backdrop of Shenzhen’s high-density urban environment, the multifunctional design of water purification plants offers dual benefits: providing residents with urban green spaces while simultaneously mitigating NIMBY sentiments due to their inherent characteristics. Unlike traditional urban development, Shenzhen’s water purification plants integrate into residents’ daily lives. Therefore, optimizing the built environment and road network structure to enhance residents’ perceptions of proximity benefits while reducing NIMBY (Not In My Backyard effect) sentiments holds significant implications for the city’s sustainable development. To address this question, this study adopted the following three-step mixed-methods approach: (1) It examined the relationships among residents’ YIMBY (Neighboring Benefits Effect) and NIMBY perceptions, perceptions of park spaces atop water purification plants, and perceptions of accessibility through questionnaire surveys and structural equation modeling (SEM), establishing a scoring framework for comprehensive YIMBY and NIMBY perceptions. (2) Random forest models and Shapley Additive Explanations (SHAP) analysis revealed nonlinear relationships between the built environment and composite YIMBY and NIMBY perceptions. (3) Spatial syntax analysis categorized the upgraded road network around the water purification plant into grid-type, radial-type, and fragmented-type structures. Scatter plot fitting methods uncovered relationships between these road network types and resident perceptions. Finally, negative perceptions were mitigated by optimizing path enclosure and reducing visual obstructions around the water purification plant. Enhancing neighborhood benefits—through improved path safety and comfort, increased green spaces and resting areas, optimized path networks, and diversified travel options—optimized the built environment. This approach proposes design strategies to minimize NIMBY perceptions and maximize YIMBY perceptions. Full article

Objective: This study aimed to explore the direct relationships between social determinants and behavioral clusters, as well as their potential indirect associations mediated by edentulism. Methods: Information on social variables (collected in Wave 3, 2006/07), edentulism (Wave 5, 2010/11), and health-related behaviors (Wave 7, 2014/15) was drawn from the English Longitudinal Study of Ageing (ELSA). Baseline sociodemographic characteristics, including age, gender, ethnicity, education, and wealth, were accounted for. Latent class analysis (LCA) was applied to four behavioral indicators—smoking status, alcohol consumption, fruit and vegetable intake, and physical activity—to identify behavioral clusters. A confirmatory factor analysis (CFA) was then used to construct a latent variable representing social support and social networks. Two structural equation models (SEM) were developed to examine both the direct associations between social support/network and behavioral clusters, and the indirect associations mediated by edentulism. Results: In LCA, the two-class model was the best fit for the data. Class 1 (risky behaviors) had 7%, while Class 2 (healthy behaviors) had 93%. In SEM Model 1, higher social support/network levels predicted being in the healthy cluster directly (SC = 0.147) and indirectly (SC = 0.009). In Model 2, accounting for wealth and education, higher levels of social support/network maintained the direct association with the healthy cluster (SC = 0.132), but the indirect path lost significance. Conclusions: This study found that greater social support was associated with healthier behaviors, and this relationship may be mediated by edentulism. Health policies that encourage social interaction could therefore improve both general and oral health. Full article