Search Results (2,103)

Bioenergy crops are widely regarded as a promising approach to support renewable energy production, diversify farm income, and enhance land-use efficiency. Despite these potential benefits, adoption rates remain low, and empirical understanding of landowners’ decision-making processes is still emerging. This study examines landowners’ interest in and likelihood of adopting bioenergy crops, explicitly differentiating between early-stage interest and near-term adoption intentions. Survey data from 207 landowners are analyzed using a bivariate probit model to identify key factors influencing both outcomes. The results reveal a marked disparity between expressed interest and adoption likelihood, with a significantly greater proportion of landowners indicating interest than those willing to adopt in the near term. Economic orientation increases adoption interest by 9.5 percentage points, while identity orientation increases adoption likelihood by 6.6 percentage points. Determinants such as increased awareness, land size, experience, and participation in conservation programs exert varying influences across different decision stages. These findings suggest that stated interest and stated near-term adoption likelihood represent related but distinct dimensions of adoption readiness, shaped by different economic, identity-based, and institutional factors. Effective promotion of bioenergy crops requires more than general awareness campaigns. Policies should combine financial incentives, technical assistance, market development support, and outreach strategies that present bioenergy crops as compatible with landowners’ economic goals, stewardship values, recreational uses, and long-term attachment to their land. Full article

Despite growing interest in Virtual Labs (VLs), limited research examines the factors influencing educators’ willingness to adopt them through the lens of inquiry-based learning (IBL). This exploratory pilot study evaluates educators’ interaction with the VHEalthLab VLs toolkit, examining their perceptions on usability, pedagogical value, IBL support, and intention to use. The study combines IBL, as a pedagogical lens, with the Technology Acceptance Model (TAM) within a Triple Bottom Line sustainability framework aligned with Sustainable Development Goals 4 and 10. Using an exploratory cross-sectional design with an embedded qualitative component, data were collected from seventy Biology educators across four European countries (Cyprus, Greece, Romania, Spain) through two structured questionnaires. Data analysis included descriptive statistics, Pearson correlations, directed content analysis, and joint display integration. Findings indicate that adoption intention was associated primarily with pedagogical rather than technological factors; IBL alignment showed the strongest association with intention to implement VLs (r = 0.63, p < 0.001), while perceived usefulness was most strongly associated with pedagogical materials (r = 0.65, p < 0.001). Assessment and inclusion functioned as quality criteria rather than factors associated with adoption intention. Educators consistently endorsed VLs as complements to physical laboratories, with their perceptions suggesting potential environmental, economic, and social sustainability implications within a blended model. Full article

Cutaneous Melanoma is a biologically heterogeneous malignancy. Although recent therapeutic advances have improved survival, durable remissions remain elusive for many patients. Surgical excision with stage-appropriate margins and selective nodal staging remains the cornerstone of curative-intent management. In contrast, conventional cytotoxic chemotherapy now plays a limited, largely palliative role given its modest efficacy and substantial toxicity. Targeted therapy with BRAF/MEK inhibitors has improved outcomes in patients with BRAF V600-mutant melanoma, resulting in rapid tumor regression and meaningful survival benefits. However, long-term disease control is frequently compromised by adaptive resistance, commonly driven by MAPK pathway reactivation or compensatory PI3K/AKT signaling. In parallel, immune checkpoint inhibitors targeting PD-1, CTLA-4, and emerging pathways have reshaped treatment across disease stages, enabling deep and sometimes durable responses. Despite this progress, primary and acquired resistance, as well as acute and chronic immune-related toxicities, continue to pose significant clinical challenges. Current therapeutic strategies focus on rational combinations of targeted therapy, checkpoint blockade, IL-2-based approaches, oncolytic viruses, and adoptive cell therapies such as tumor-infiltrating lymphocytes to enhance response depth and durability. However, these intensified regimens carry increased toxicity risks, highlighting the need for improved patient selection and monitoring. Overall, emerging evidence supports a paradigm shift toward optimized treatment sequencing, response-adapted surgical strategies, and biomarker-guided personalization to maximize clinical benefit while minimizing toxicity. Full article

Background/Objectives: Artificial Intelligence (AI) integration in healthcare promises improved diagnostic accuracy, patient safety, and operational efficiency. However, AI acceptance among healthcare workers remains limited due to knowledge gaps, risk concerns, and governance challenges, particularly in developing countries like Saudi Arabia, where rapid healthcare modernization faces unique infrastructure, organizational, and cultural challenges. This research investigates the factors influencing AI acceptance among medical practitioners, nurses, administrators, and students in Saudi Arabian hospitals to identify key determinants and barriers to adoption. Methods: This cross-sectional study employed an extended Unified Theory of Acceptance and Use of Technology (UTAUT) framework integrated with ethical considerations from the Model for Ethical Assessment and Analysis of AI in Medicine (MEAAM). A structured bilingual questionnaire was administered to 119 healthcare professionals and students across Saudi Arabia, measuring constructs including Awareness and Knowledge, Performance Expectancy, Effort Expectancy, Facilitating Conditions, Social Influence, Trust, Perceived Risk, Ethical Governance, and Price Value. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed for quantitative analysis, supplemented by thematic analysis of open-ended qualitative responses. Results: The PLS-SEM analysis explained 59.8% of variance in behavioral intention to adopt AI (R² = 0.598). Awareness and Knowledge emerged as the strongest predictor (β = +0.505, p < 0.001), followed by Performance Expectancy (β = +0.229, p < 0.05) and Social Influence (β = +0.123). Perceived Risk functioned as the primary barrier (β = −0.185, p < 0.05). Qualitative findings identified infrastructure gaps, regulatory ambiguities, and training deficiencies as major implementation barriers, while emphasizing opportunities in diagnostic accuracy and remote monitoring. Conclusions: AI acceptance in Saudi healthcare is primarily driven by knowledge, with perceived usefulness and peer support as secondary facilitators, while safety and accountability concerns remain substantial obstacles. Successful AI integration requires coordinated efforts in education, transparent governance frameworks, and institutional support. This study contributes theoretically by validating extended UTAUT in a non-Western healthcare context and practically by providing evidence-based strategies for sustainable AI adoption that enhance healthcare quality while respecting professional roles and ethical principles. Full article

Background: Public healthcare systems face persistent workforce retention challenges that undermine service continuity, organizational resilience, and public value creation. Although leadership is frequently identified as a relevant lever, the literature remains theoretically fragmented and often treats leadership effects as direct and context-free. Methods: This review adopts a PRISMA-guided systematic literature review as a theory-building strategy. Searches were conducted in Web of Science, Scopus, and PubMed using combinations of terms related to leadership, organizational commitment, job satisfaction, turnover intention, and retention in healthcare settings. The review identified 640 records, removed 372 duplicates, screened 268 titles and abstracts, assessed 90 full-text records for eligibility, and retained 30 peer-reviewed studies for configurative synthesis. The analysis combined thematic synthesis with configurative mapping to identify mechanisms, recurring patterns, and contextual contingencies. Results: The review shows three consistent patterns. First, leadership is linked to retention predominantly through organizational commitment, especially affective and normative commitment, rather than through direct effects. Second, institutional and organizational conditions—particularly red tape and working conditions—shape the strength of leadership–commitment relationships. Third, workforce heterogeneity, including generational differences, affects how leadership practices and organizational environments are interpreted, although these dynamics are rarely theorized explicitly in the literature. Conclusions: The article develops a governance-sensitive integrative framework in which people-centered leadership influences turnover intentions indirectly through organizational commitment, while red tape and working conditions operate as contextual moderators. By embedding leadership within Public Administration and governance theory, the review clarifies the literature’s main explanatory gap and provides a foundation for comparative empirical testing and for more sustainable workforce strategies in public healthcare systems. Full article

This study examines the structural determinants of behavioral intention to use a City Airport Terminal (CAT) in Ulsan using a structural equation modeling (SEM) framework. Whereas prior literature has predominantly explained CAT adoption in terms of accessibility, this study investigates whether usage intention can be sufficiently explained by accessibility alone or whether it reflects a broader multi-factor structure involving service quality and safety, economic efficiency, infrastructure convenience, and perceived public value. To this end, five latent constructs were specified, and a survey of 500 Ulsan residents was conducted. The confirmatory factor analysis indicated an acceptable measurement structure for the five latent constructs. The structural model results show that perceived public value and regional development was the only construct with a statistically significant direct path to CAT usage intention, whereas the baseline accessibility-only model provided a statistically insufficient explanation. A nested model comparison further indicated that non-accessibility constructs collectively contributed additional explanatory value beyond what accessibility alone could provide. These findings suggest that CAT usage intention is not adequately explained by accessibility alone but is better understood through a multi-factor conceptualization of CAT adoption. This study contributes to the literature by providing structural evidence that public value—encompassing regional development expectations and community-level benefits—should be explicitly considered in sustainable airport infrastructure planning. The results highlight the importance of a multi-dimensional approach to CAT implementation policy, integrating service quality and safety, economic efficiency, infrastructure convenience, and community-level value perceptions alongside physical accessibility. From a sustainable mobility perspective, the findings offer useful implications for sustainable airport access planning and air transport management. Full article

As transportation-related environmental pressures intensify, understanding the psychological mechanisms underlying battery electric vehicle (BEV) adoption has become increasingly important. Drawing on the Value–Attitude–Behavior (VAB) framework, this study investigates how perceived green value, hedonic value, and utilitarian value shape Chinese consumers’ attitudes and purchase intentions toward BEVs, while examining the moderating roles of technophilia, range anxiety, and battery cost. A cross-sectional online survey was conducted in China, yielding 596 valid responses. Partial Least Squares Structural Equation Modeling (PLS-SEM) and Necessary Condition Analysis (NCA) were employed for data analysis. The results show that perceived hedonic value exerts the strongest positive effect on Attitude Toward Using BEVs (β = 0.591, p < 0.001), followed by perceived utilitarian value (β = 0.135, p < 0.001) and perceived green value (β = 0.074, p = 0.026). Attitude Toward Using significantly predicts BEV purchase intention (β = 0.151, p = 0.002). Technophilia significantly moderates the relationship between attitude and purchase intention (β = −0.096, p = 0.002), whereas the moderating effects of range anxiety and battery cost are not significant. The structural model explains 40.9% of the variance in attitude and 24.2% of the variance in purchase intention. NCA results further reveal that hedonic value constitutes the most critical necessary condition for forming favorable attitudes toward BEVs (d = 0.079, p < 0.001). This study contributes to the sustainable mobility literature by extending the VAB framework through the integration of multidimensional perceived value and necessary condition logic within the Chinese BEV context. The findings highlight that experiential and technological enjoyment, rather than environmental concern alone, has become a central driver of BEV adoption in emerging electric mobility markets. Full article

Digital transformation in construction small and medium-sized enterprises (SMEs) depends on employees’ willingness to use information systems in their daily work. This study examines the role of transformational leadership (TL) and perceived organizational support (POS) in employees’ behavioral intention to use information systems in Chinese engineering construction SMEs. It also considers the mediating role of perceived usefulness (PU) and perceived ease of use (PEOU) and the moderating role of organizational culture. A total of 361 valid responses were collected from employees in Chinese engineering construction SMEs. The results show that TL and POS both act as organizational drivers of employees’ adoption intention. TL influences BI by improving employees’ cognitive evaluation of information systems through PU and PEOU. POS provides resource-based support to help employees feel more confident using these systems. OC further conditions how employees respond to leadership and support signals during digital transformation. These findings suggest that technology acceptance in engineering construction SMEs is shaped by both individual technology beliefs and organizational conditions. This study extends technology acceptance research by making the Theory of Planned Behavior more concrete through managerial and support mechanisms. It also provides practical guidance for SME managers seeking to support digitalization through clear leadership communication, targeted resource support, and a learning-oriented culture. Full article

Background/Objectives: Remote monitoring (RM) of cardiac implantable electronic devices (CIEDs) has been associated with potential clinical and economic benefits; however, its adoption among patients remains limited in some healthcare settings. This study examined patients’ intention to use RM services by applying an extended Technology Acceptance Model (TAM) that incorporates perceived effectiveness (PE), perceived barriers (PB), perceived threat (PT), and economic considerations, as well as the influence of socioeconomic factors. Methods: A cross-sectional survey was conducted among 104 patients with CIEDs in Taiwan using validated questionnaires. Structural equation modeling (SEM) was employed to examine the relationships among the proposed constructs. The association between intention to use and actual service utilization was explored. The correlations between sociodemographic factors and the constructs were analyzed using analysis of variance (ANOVA). Results: SEM showed that perceived effectiveness (PE), perceived usefulness (PU) and perceived ease of use (PEOU) were significantly associated with intention to use RM services, with economic considerations also having a significant contribution. Intention to use RM services further predicted actual adoption. However, PB and PT did not moderate these relationships. Sociodemographic factors influenced RM acceptance, with younger, more educated, employed, higher-income, and professionally employed patients reporting stronger perceptions and greater intention to use RM. Conclusions: This study reinforces the TAM framework in the context of health-related technology adoption. Overall, the adoption of RM services is complex and shaped by psychological, economic, and demographic factors, highlighting the need for user-friendly design, targeted education on clinical benefits, and flexible pricing and reimbursement strategies to improve equitable and sustained use. Full article

The adoption of large language models (LLMs) is reshaping how organizations approach automation, decision-making, and user engagement across sectors. This study investigates the trends, theoretical frameworks, and adoption factors influencing the integration of LLMs in five key domains: education, commerce, banking, healthcare, and service. By employing a systematic literature review and meta-analysis, this paper synthesizes research published between 2022 and early 2026, corresponding to the period when LLMs became widely accessible for public and enterprise use, to evaluate both conceptual and empirical dimensions of LLM adoption. The review identifies the Technology Acceptance Model and the Unified Theory of Acceptance and Use of Technology, including its extensions, as the most frequently applied frameworks. It also highlights the growing incorporation of complementary models such as the diffusion of innovation, the information system success model, and self-determination theory. The meta-analysis examines 59 pairwise relationships drawn from 154 studies with a cumulative sample size of 88,886 participants. Using correlation coefficients, $I^2$ statistics, and Egger’s test, the analysis reveals strong, consistent associations between behavioral intention and both use behavior and actual use, while also identifying high heterogeneity across contexts. Constructs such as trust, hedonic motivation, and personal innovativeness emerged as influential but were underrepresented in the theoretical modeling. The study underscores the importance of facilitating conditions, infrastructure, and organizational readiness for enabling sustained use while also drawing attention to gaps in addressing perceived risks, privacy concerns, and ethical implications. Full article

Developing-country construction sectors continue to record disproportionately high occupational accident rates, partly attributable to the slow adoption of digital safety technologies, including Building Information Modeling (BIM) and Internet of Things (IoT) systems. While prior empirical research has established the population-level factors that explain stakeholder adoption intention through survey-based frameworks, the ability to classify individual stakeholder readiness for targeted, pre-deployment intervention remains methodologically unaddressed. This study fills that gap by applying three supervised machine learning classifiers (Random Forest [RF], XGBoost (XGB), and Support Vector Machine (SVM)) to a dataset of 107 construction professionals purposively sampled from large-scale infrastructure projects in Pakistan, including China−Pakistan Economic Corridor (CPEC) packages and the Barakahu Bypass project. Five construct-level features derived from an integrated Technology Acceptance Model and Technology−Organization−Environment (TAM-TOE) survey instrument were used to classify stakeholders into High, Moderate, and Low readiness tiers. XGBoost achieved the best classification performance (accuracy = 93%, macro F1 = 0.93), followed by RF (91%, F1 = 0.91) and SVM (87%, F1 = 0.87). The convergent performance across three structurally different algorithm families indicates that the readiness signal reflects a consistent attitudinal pattern rather than an artifact of any single modeling assumption. Feature importance analysis consistently identified Perceived Benefits (32%) and Technology Awareness (25%) as the dominant predictive features, followed by Organizational Readiness (20%), Perceived Barriers (15%), and Respondent Profile (8%). Attitudinal readiness mapping classified 62% of stakeholders as High readiness, 28% as Moderate, and 10% as Low, providing an exploratory attitudinal segmentation framework to assist construction managers in prioritizing capacity-building investments, subject to longitudinal behavioral validation. The study also finds that awareness of digital technology consistently outpaces Organizational Readiness for implementation, a pattern consistent with findings from analogous developing-country construction contexts. Full article

Multimodal artificial intelligence-generated content (AIGC) is reshaping museum digital exhibitions through dynamic content generation, contextual storytelling, and interactive feedback. Despite its growing adoption, the impact of AIGC’s experiential attributes on visitors’ digital exhibition experience intention remains underexplored. Drawing on the Technology Acceptance Model (TAM), this study develops an integrative framework incorporating AIGC technology acceptance, perceived immersion, content creativity, interaction quality, cognitive evaluations, and affective responses. Data were collected from 481 visitors with prior digital exhibition experience and analyzed using PLS-SEM. The results indicate that AIGC technology acceptance significantly influences perceived ease of use, perceived usefulness, and digital exhibition experience intention; interaction quality enhances usability and exerts a direct effect on intention; and immersion and content creativity primarily shape intention through perceived enjoyment while also exhibiting direct effects. These findings extend TAM to multimodal AIGC-enabled museum contexts and provide empirical evidence to guide the design of culturally meaningful, interactive, and engaging digital exhibition experiences. Full article

This paper addresses the critical challenge of accelerating the adoption of sustainable innovations by examining the interdependence between managerial credibility and consumer pragmatism. The aim of the study was to investigate how perceived trust in management influences purchase intention, specifically analysing both the mediating role of financial perceptions and the moderating effect of digital literacy. The study had a quantitative approach, with data being collected from 408 Romanian respondents. The statistical analysis was performed using JASP software (version 0.96.0.0), applying both multiple and simple linear regression as well as a mediation analysis (SEM). The results indicate that both perceived trust in management and the perception of innovation as an investment directly stimulate purchase intention such that that credible management can convince consumers of the financial benefits. However, even though digital literacy plays a fundamental role in consumers’ lives, it does not affect the relationship between managers’ credibility and the willingness to buy sustainable products. The paper concludes that for sustainable innovations to be financially successful, organisations must move beyond the green labelling and focus on building genuine strategic credibility. Therefore, these findings offer valuable insights for both managers and policymakers in their efforts to support the transition to a more sustainable market. Full article

The existing literature highlights that artificial intelligence (AI) creates both hope and threat perceptions among managers and workers, particularly due to concerns about potential job losses and the negative effect on continued professional development. Employee trust in AI-based systems varies depending on their features and performance. Furthermore, regardless of the performance of such systems, some individuals are inherently opposed to AI, a phenomenon known as AI aversion. In this study, an Integrative AI Adoption Framework is developed, drawing upon principles from established theories, including the technology acceptance model, behavioral decision theory, and emotion-based frameworks, to assess how perceived usefulness and perceived ease of use, along with perceived threat, trust, and AI aversion, influence human resources (HR) professionals’ attitudes and behavioral intentions to use AI-based recruitment systems. In doing so, the study conceptualizes AI-based recruitment as a socio-technical system in which a technical subsystem (the system’s instrumental and AI-specific properties) and a social subsystem (the affective and trust-related responses of HR professionals) must be jointly considered to explain adoption. The model was tested using the partial least squares structural equation modeling (PLS-SEM) approach through survey-based data collected from 242 HR professionals. The study’s findings indicate that attitude plays an important role in shaping behavioral intention, and perceived usefulness is a key driver of attitude. AI aversion negatively influences attitudes, while trust has a twofold effect of reducing AI aversion and positively influencing attitude. Additionally, perceived threat significantly increases AI aversion, which is driven by concerns over job replacement and personal development. Full article

Population ageing is reshaping the assumptions on which succession law has traditionally rested. This article examines how Spanish succession law responds to this demographic shift through two closely connected dimensions: testamentary capacity and the growing role of succession agreements. The analysis adopts a doctrinal and comparative perspective within the Spanish legal system, taking account of the coexistence of the Spanish Civil Code and several autonomous succession regimes. It argues that testamentary capacity remains governed by a deliberately low and functional threshold, centred on the testator’s actual ability to form and express a testamentary intention at the time of execution, and that notarial ex ante control is central to preserving both autonomy and legal certainty. At the same time, relational vulnerability in later life requires distinct safeguards aimed at preserving testamentary freedom. The article further shows that succession agreements, often viewed as restrictions on testamentary freedom, may also operate as instruments of anticipatory autonomy. The central challenge is to make autonomy effective across time without confusing vulnerability with incapacity, or protection with constraint. Full article