Search Results (369)

As a neighborhood-scale derivative of the Business Improvement District (BID) model, the Neighborhood Business Improvement District (NBID) represents a collaborative governance framework aimed at fostering spontaneous urban regeneration. Its successful establishment critically depends on building consensus among diverse stakeholders during the preparatory phase. This study addresses a significant gap by investigating the psychological mechanisms that shape stakeholders’ willingness to engage in NBIDs prior to their formation. Employing an exploratory sequential mixed-methods approach, we conducted semi-structured interviews in the Tiyuan North Community (Tianjin) and the Yulin East Road Community (Chengdu). Insights from the qualitative phase informed a subsequent quantitative survey administered to 215 stakeholders in Tianjin. Data were analyzed using regression analysis and Structural Equation Modeling (SEM). The results reveal that stakeholders’ performance expectations and collaborative willingness are significantly influenced by three core confidence factors: “Confidence in Authority Support (AS)” (particularly “Confidence in Council Representation”), “Confidence in Organization Capability (OC)” (especially “Confidence in Coordination Ability”), and “Confidence in Multi-party Collaboration.” Crucially, “Confidence in Enabling collaboration (MC_3)” itself acts as a key mediator, translating institutional trust into performance expectations. This study contributes a novel “Confidence–Expectation” framework to the literature on collective action and offers practical, context-sensitive insights for designing collaborative community governance structures aimed at sustainable urban regeneration in China and beyond. Full article

Organisations increasingly combine social innovation and environmentally orientated technologies in response to sustainability and stakeholder pressures. However, empirical evidence remains limited on how organisational actors perceive and cognitively associate social innovation, green technologies, and practices related to the Sustainable Development Goals (SDGs), particularly in emerging European economies. This study addresses this gap by examining whether employees and managers perceive these dimensions as interconnected and whether green technologies represent a statistically significant indirect association between social innovation and SDG-related organisational practices. Using a cross-sectional online survey of 265 employees and managers from Romanian companies in production, services, IT, and commerce, we estimated an exploratory structural model through partial least squares structural equation modelling (PLS-SEM). The results reveal strong positive associations between perceived social innovation and SDG-related organisational practices, as well as between perceived social innovation and green technologies. Green technologies are also positively associated with SDG-related practices and exhibit a statistically significant indirect association within the observed pattern of associations. Consistent with perception-based research design, these findings suggest that respondents cognitively group social and technological initiatives as complementary components of a broader sustainability orientation, rather than indicating statistical or process-based mechanisms. The study contributes to organisational sustainability research by integrating social innovation and green technologies within a single organisational-level framework and by providing context-specific evidence from Romania, an under-represented central and Eastern European context. Full article

The purpose of this study was to develop and validate an integrated model explaining how AI-enabled knowledge integration and digital ecosystem connectivity influence knowledge innovation capability through the mediating role of knowledge agility and the moderating roles of digital trust and organizational learning culture. Grounded in the Knowledge-Based View (KBV) and Dynamic Capability Theory (DCT), this research seeks to understand how technological and cultural enablers jointly drive exploratory, exploitative, and adaptive innovation. A quantitative cross-sectional research design was employed, and data were collected from 243 professionals working in knowledge-intensive organizations. Measurement scales were adapted from previous studies, and data analysis was conducted through structural equation modeling, using SmartPLS 4. Reliability, validity, and path analyses were performed to test the hypothesized relationships among constructs. The results indicated that AI-enabled knowledge integration and digital ecosystem connectivity significantly enhance knowledge agility, which in turn positively affects knowledge innovation capability. The mediation tests confirmed the role of knowledge agility, while digital trust and organizational learning culture were confirmed to strengthen the relationship between knowledge agility and innovation capability. This study contributes to theory by integrating technological, organizational, and cultural perspectives into a unified model of digital innovation. Practically, it guides organizations in leveraging AI systems, digital connectivity, and learning culture to foster sustainable innovation. Full article

Background: Rural healthcare providers encounter multifaceted barriers including geographic isolation, resource limitations, and provider shortages that impede optimal patient care delivery. The Barriers Experienced in Providing Healthcare Instrument (BTCPI) was designed to assess provider challenges; however, concerns regarding its psychometric properties necessitated comprehensive validation. The primary purpose of the study was to evaluate the structural validity of the instrument using confirmatory factor analysis with a sample of Idaho healthcare professionals. Because the model failed to meet criteria, the study identified a more parsimonious model that then underwent multi-group invariance testing. Methods: A survey consisting of a modified Barriers to Providing Optimal Healthcare instrument and a demographic questionnaire was distributed to Idaho healthcare providers across 22 clinical sites in the state. The structural validity of the modified 41-item, 9-factor instrument was assessed using confirmatory factor analysis (CFA), exploratory structural equation modeling (ESEM), and exploratory factor analysis (EFA). Multi-group invariance testing was also conducted to assess measurement equivalence across provider profession, practice setting (rural vs. urban), and years of experience. Results: A total of 373 healthcare providers completed the survey and were used for analysis. The proposed BTCPI model did not meet model fit criteria. An ESEM analysis was conducted and identified a 9-factor, 14-item model. However, due to fit concerns, an exploratory factor analysis was subsequently conducted and identified the 4-factor, 12-item (BPOC-12) that also met invariance criteria across groups. A group mean and variance differences were found between nurses and primary care providers as well as between rural and urban practitioners on several barrier factors. Conclusions: The BTCPI did not meet model fit criteria. Subsequent model refinement resulted in the BPOC-12, which had preliminary psychometric validity. Although the refined model offered a more condensed and preliminarily valid psychometric framework, future research should be done to assess this model. Future research should also collect responses from different healthcare professions to enhance its applicability. Full article

This study attempts to examine the interconnections between digital transformation, leadership, organizational culture, and organizational sustainability among Greek enterprises in the Industry 4.0 context. A quantitative research design was utilized to attain this objective, employing survey data gathered from 412 managerial-level participants across several industries. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were performed to validate the measurement model, followed by Structural Equation Modeling (SEM) to examine the proposed correlations among the constructs. The findings reveal that digital transformation, leadership, and organizational culture each have a substantial positive influence on organizational sustainability, with digital transformation exhibiting the most pronounced benefit. Furthermore, their alignment has a synergistic effect that amplifies the economic, social, and environmental aspects of sustainability. These findings validate the multifaceted character of sustainability within the Industry 4.0 framework and underscore the interrelation of technological, human, and cultural competencies. The research contributes to the field of theory by offering a comprehensive framework for sustainable organizational transformation and practical implications for managers and policymakers who are in the process of developing strategies that are oriented towards sustainability, innovation, and resilience in digitally evolving environments. Full article

This study developed and validated the Human–Computer Collaborative Classroom Second Language Learning Engagement Scale among 710 junior high school students studying in Mongolian. Initially, the scale’s conceptual framework was developed through a review of pertinent literature and interview, drawing on self-determination theory and socio-constructivist perspectives to define engagement in human–computer collaborative second language learning contexts. The study adopted a sequential mixed-methods design: in Phase 1, item analysis and exploratory factor analysis (EFA) were conducted using data from 437 students, resulting in a preliminary five-factor structure; in Phase 2, confirmatory factor analysis (CFA) was performed using data from the remaining 273 students to validate the factor structure. The final scale comprises five core dimensions: (1) higher-order thinking, (2) student–teacher interaction, (3) human–computer interaction, (4) active collaborative learning, and (5) learning enthusiasm. Structural equation modeling confirmed a robust five-factor model, with all fit indices indicating satisfactory model fit (e.g., CFI = 0.981, TLI = 0.977, RMSEA = 0.041). The scale demonstrates strong internal consistency (Cronbach’s α = 0.959) and construct validity. These findings highlight the reliability and efficacy of this psychometric tool for evaluating students’ engagement in second language learning within human–computer collaborative classroom environments, offering valuable insights for educators and researchers. Full article

Background: Glioblastoma (GBM) is among the most aggressive and morphologically heterogeneous brain tumors. Beyond static imaging biomarkers, its structural organization can be viewed as a nonlinear dynamical system. Characterizing morphodynamic attractors within such a system may reveal latent stability patterns of morphological change and potential indicators of morphodynamic organization. Methods: We analyzed 494 subjects from the multi-institutional BraTS 2020 dataset using a fully automated computational pipeline. Each multimodal MRI volume was encoded into a 16-dimensional latent space using a 3D convolutional autoencoder. Synthetic morphological trajectories, generated through bidirectional growth–shrinkage transformations of tumor masks, enabled training of a contraction-regularized Neural Ordinary Differential Equation (Neural ODE) to model continuous-time latent morphodynamics. Morphological complexity was quantified using fractal dimension (DF), and local dynamical stability was measured via a Lyapunov-like exponent (λ). Robustness analyses assessed the stability of DF–λ regimes under multi-scale perturbations, synthetic-order reversal (directionality; sign-aware comparison) and stochastic noise, including cross-generator generalization against a time-shuffled negative control. Results: The DF–λ morphodynamic phase map revealed three characteristic regimes: (1) stable morphodynamics (λ < 0), associated with compact, smoother boundaries; (2) metastable dynamics (λ ≈ 0), reflecting weakly stable or transitional behavior; and (3) unstable or chaotic dynamics (λ > 0), associated with divergent latent trajectories. Latent-space flow fields exhibited contraction-induced attractor-like basins and smoothly diverging directions. Kernel-density estimation of DF–λ distributions revealed a prominent population cluster within the metastable regime, characterized by moderate-to-high geometric irregularity (DF ≈ 1.85–2.00) and near-neutral dynamical stability (λ ≈ −0.02 to +0.01). Exploratory clinical overlays showed that fractal dimension exhibited a modest negative association with survival, whereas λ did not correlate with clinical outcome, suggesting that the two descriptors capture complementary and clinically distinct aspects of tumor morphology. Conclusions: Glioblastoma morphology can be represented as a continuous dynamical process within a learned latent manifold. Combining Neural ODE–based dynamics, fractal morphometry, and Lyapunov stability provides a principled framework for dynamic radiomics, offering interpretable morphodynamic descriptors that bridge fractal geometry, nonlinear dynamics, and deep learning. Because BraTS is cross-sectional and the synthetic step index does not represent biological time, any clinical interpretation is hypothesis-generating; validation in longitudinal and covariate-rich cohorts is required before prognostic or treatment-monitoring use. The resulting DF–λ morphodynamic map provides a hypothesis-generating morphodynamic representation that should be evaluated in covariate-rich and longitudinal cohorts before any prognostic or treatment-monitoring use. Full article

Background: Interactions between healthcare professionals and medical technology companies on social media are central to understanding how variations in knowledge spillover and innovation performance vary. Aim: This study investigates how social media facilitates knowledge exchange between these two stakeholder groups in Austria, drawing on a cross-sectional online survey of 97 participants (45 healthcare professionals and 52 medical technology company representatives). Data were analyzed using Confirmatory Factor Analysis (CFA), Exploratory Structural Equation Modeling (ESEM), and independent-samples t-tests. The comparative approach enabled the identification of structural differences across stakeholder groups and regions within Austria. Methodology: The study adopts a comparative analysis framework to explore geographic differences within Austria and to examine how social media interaction strengthens dense and strong network ties between healthcare professionals and medical technology companies, thereby enhancing information-processing capabilities. Results: The findings underscore the pivotal role of social media in bridging geographic boundaries, fostering dense and strong network ties, and enhancing information-processing capacities. Conclusions: This study advances the understanding of how digital interaction mechanisms shape knowledge exchange and innovation performance in healthcare outcomes. Practical Implications: The findings suggest that social media promotes stronger professional relationships and deeper customer engagement. The results may assist policymakers and industry leaders aiming to design effective digital strategies for innovation and improved healthcare outcomes. Full article

Workplace behaviors and employee outcomes, such as team functioning, job satisfaction, and intentions to leave, are crucial for healthcare quality and safety. It highlights the substantial productivity, societal, and economic costs of worker well-being. Against this backdrop, this study examines how two dimensions of organizational culture: ethical climate and perceived managerial competence, together with team support, relate to job satisfaction and turnover intention among healthcare professionals. A quantitative, cross-sectional survey was conducted with 430 physicians, nurses, and other clinical staff in public and private institutions across the Federation of Bosnia and Herzegovina. Using established scales and structural equation modeling (SEM) in AMOS, we first verified satisfactory reliability and construct validity via exploratory and confirmatory factor analyses. The structural model showed that ethical organizational culture and managerial competence are positively related to team support and, directly or indirectly, to higher job satisfaction and lower turnover intention. Team support was positively related to job satisfaction and negatively related to turnover intention and significantly mediated the effects of both ethical climate and managerial competence on these outcomes. In addition, job satisfaction was strongly and negatively correlated with turnover intention, underscoring its central role in retention. Full article

Effective stakeholder management is essential in construction projects, but numerous context-specific challenges often hinder its implementation. This study investigates the factors that limit stakeholder management in Türkiye’s construction industry through a structured, multi-stage analytical approach. A systematic literature review first identified 69 stakeholder management challenges (SMCs). A questionnaire administered to 164 construction professionals was then analyzed using the normalized mean value (NMV) approach, which identified 53 critical challenges (CCs). To reduce the dimensionality of the 53 CCs, exploratory factor analysis (EFA) was conducted, resulting in four overarching factors: (1) weak planning, coordination, and implementation deficiencies; (2) institutional and operational weaknesses; (3) communication problems; and (4) legal regulations, bureaucratic barriers, and ethical issues. Finally, structural equation modeling (SEM) was applied to highlight the effect sizes of these factors in stakeholder management, rather than to perform predictive modeling. The results show that institutional and operational weaknesses and communication problems exert the strongest negative influences. By clearly linking the 53 CCs with four higher-level factors, this study provides a coherent analytical structure and a robust methodological basis for understanding the barriers to effective stakeholder management. The findings offer actionable insights for construction practitioners and policymakers seeking to enhance coordination, communication, and governance mechanisms in complex project environments. Full article

To promote material circularity and a sustainable built environment, this study investigates the application of industrial waste within South Africa’s built environment, with a focus on civil engineering projects. A post-positivist philosophical stance was adopted, with a quantitative method and a structured questionnaire used for data collection. Responses were solicited from built environment professionals involved in the delivery of civil engineering projects, and the data gathered were analysed using appropriate descriptive and inferential statistics, including exploratory factor analysis and partial least squares structural equation modelling (PLS-SEM). Findings revealed that, despite increased awareness of recycled construction and demolition waste, fly ash, and foundry sand, among others, their use remains limited due to three significant constraints. These are (1) knowledge, skills, and awareness, (2) operational and regulatory, and (3) governance and industry collaboration. PLS-SEM further showed that prioritizing sustainable practices and fostering multidisciplinary collaboration are the most significant strategies for enhancing industrial waste usage in the country. Practically, the study indicates that overcoming regulatory, knowledge, and operational issues through targeted policies, infrastructure investments, and collaborative efforts can significantly promote material circularity and sustainability in the South African built environment. Theoretically, the findings offer valuable insights for future studies on the application of industrial waste in the delivery of built environment projects in developing countries, where such studies have not been explored. Full article

Three-dimensional printed food has rapidly positioned itself at the intersection of food technology and personalized nutrition, opening up new perspectives for sustainable production, creative customization, and more efficient resource use. Although global interest in this innovation continues to grow, consumer acceptance remains largely underexplored in Central and Eastern Europe. This study analyzes how Romanian consumers approach the adoption of 3D-printed food by applying an extended UTAUT2 framework to a sample of 608 urban respondents. Using structural equation modeling, it examines the influence of expected effort, performance expectancy, social influence, and perceived compatibility on adoption intention, while price perception is introduced as a key mediating variable—a novel and meaningful contribution to the literature on food technology acceptance. Given the non-probabilistic sampling design, the difficulties encountered in measuring Hedonic Motivation and Facilitating Conditions, and the early diffusion stage of 3D food printing in Romania, the present work should be viewed as a robust exploratory investigation based on Structural Equation Modeling (SEM) among urban Romanian consumers, providing first empirical evidence on 3D-printed food acceptance in Eastern Europe rather than definitive conclusions for the entire population. The results highlight that utilitarian and social factors are decisive: expected effort enhances perceived performance, while performance, social influence, and compatibility significantly strengthen perceptions of price fairness. In turn, price perception strongly predicts consumers’ behavioral intention to adopt 3D-printed food. Hedonic motivation and facilitating conditions were not statistically significant and were therefore removed from the final model. These findings show that, in emerging food markets, consumers tend to make adoption decisions based more on rational value assessments than on novelty or convenience. The study contributes to theory by embedding price perception into the UTAUT2 framework and to practice by identifying the key elements that can boost market readiness—transparent pricing and closer alignment with consumer values. By filling an important gap in the empirical literature from Eastern Europe and focusing on price as a cognitive bridge between technological and psychological drivers, this paper offers a timely and relevant contribution to ongoing research on consumer perception and acceptance of food innovations. For Eastern European food innovation research, this study provides one of the first quantitative analyses of 3D-printed food acceptance that explicitly links technology-related beliefs to price perception in a regional, price-sensitive context. Full article

Migrant construction workers make up a significant portion of the workforce in many countries and play a crucial role in alleviating the skilled labor shortage. Although vocational education and training (VET) is essential for equipping these workers with the skills needed to enhance workforce quality and bridge the skills gap, their intentions to attend VET (IAVET) remain relatively low. Drawing on the theory of planned behavior (TPB), this study investigates the antecedents of IAVET among migrant construction workers and explores the moderating role of work pressure. A questionnaire survey was conducted among 547 construction workers in China, followed by exploratory factor analysis, confirmatory factor analysis, and structural equation modeling. The results show that social support has a significant positive correlation with IAVET. Moreover, the three planned behavioral factors mediate the relationship between social support and IAVET, with the mediating effects varying depending on the level of work pressure experienced by workers. Notably, subjective norms (SN) emerge as the strongest mediator, while work pressure (WP) significantly moderates both the direct and indirect pathways, highlighting their critical roles in shaping VET participation intentions. These findings provide valuable insights into the mechanisms through which social support influences migrant construction workers’ IAVET, offering practical implications for improving workforce skills and addressing the skilled labor shortage in the construction sector and similar industries worldwide. Overall, the study strengthens the theoretical explanatory power of the extended TPB framework and offers actionable guidance for policymakers and construction enterprises to enhance migrant workers’ engagement in VET. Full article

As sustainability becomes central to tourism, tourists are no longer passive consumers but active stakeholders who influence organizational behavior. This study investigates how green consumer behavior (GCB) shapes expectations for employee green competencies and organizational sustainability strategy (OSS). Data were collected through a structured survey of 326 domestic tourists in Albania. Green skills expectation (GSE) was modeled as a latent construct derived from two observed variables: green loyalty and brand image, and willingness to support sustainability. Statistical analyses included exploratory factor analysis (EFA), K-means clustering and structural equation modeling (SEM). GCB significantly predicted both OSS and GSE, confirming that green tourists influence how organizations structure and communicate their sustainability practices. Cluster analysis identified two consumer profiles: committed eco-tourists and green-adaptive tourists. This study advances current understanding of how tourists act as external agents of internal organizational change. It extends the theoretical discourse on green marketing and sustainable workforce development by positioning tourist expectations as a driver of human resource transformation. The findings offer meaningful implications for tourism operators, educators and policymakers seeking to align employee training and service delivery with the demands of sustainability-oriented travelers. In this way, the study bridges the gap between consumer behavior and workforce development, contributing to a more integrated approach to sustainable tourism. Full article

Background: Low back pain (LBP) profoundly impacts daily life, requiring assessment tools that capture its complex effects on the body and mind. This study explores a measurement tool designed to assess LBP disability, testing whether Exploratory Structural Equation Modeling (ESEM) better reveals its multidimensional nature compared to Confirmatory Factor Analysis (CFA). Methods: We analyzed data from 266 LBP patients using CFA and ESEM. The tool, developed from the items from existing scales, included 99 questions on body functions, activities, and participation. Using Mplus 8 software, we compared model fit and item connections. Results: Two main factors; “Body Functions” and “Activity-Participation” identified by CFA were tested using ESEM. While ESEM had slightly better fit compared to CFA model, many items linked across both factors which shows how pain and emotions overlap with daily activities. These results align with the International Classification of Functioning, Disability and Health (ICF) and reflect LBP’s broad impact. Conclusions: ESEM offers a broader understanding of LBP’s multidimensional nature compared with CFA, guiding clinicians to create a holistic management approach that address physical and psychosocial challenges. This preliminary study supports the use of ESEM in disability research, demonstrating its usefulness in identifying the multifaceted nature of LBP, therefore providing a broader perspective for assessment and management. Full article