Search Results (5,059)

This study investigated Chinese EFL students’ behavioral intentions to learn English using AI-based chatbots. A total of 1052 questionnaire responses were collected from Chinese students. Structural equation modeling (SEM) was employed to assess the measurement model and test the proposed relationships. The results showed that facilitating conditions, social influence, performance expectancy, and effort expectancy were salient factors associated with students’ intentions to use AI chatbots. These UTAUT factors were also significantly related to information quality and AI trust. Information quality was positively associated with both AI trust and intention to use, while AI trust was directly associated with behavioral intention. In addition, information quality and AI trust mediated the relationships between the UTAUT factors and behavioral intention. Moderation analysis indicated that technological consciousness positively moderated the relationship between information quality and behavioral intention, but did not moderate the relationship between AI trust and behavioral intention. Internet experience also strengthened the positive relationships between information quality, AI trust, and behavioral intention. Finally, theoretical and practical implications are discussed, and limitations are highlighted. Full article

Learning agility has become an essential capability for employees working in technology-driven environments characterized by rapid change and uncertainty. Despite increasing attention on learning agility, limited empirical research has examined how different levels of cognitive abilities contribute to its development, particularly among Generation Z employees. This study investigates the cognitive determinants of learning agility by distinguishing between basic cognitive abilities and high-level cognitive abilities and examining their roles across established and start-up companies. A total of 270 Generation Z employees in Indonesia participated in the study, consisting of 135 employees from established companies and 135 from start-up companies. Cognitive abilities were assessed using objective psychometric instruments, where basic cognitive abilities (reasoning, memory, attention, coordination, and perception) were measured using CogniFit, while high-level cognitive abilities were assessed through the Divergent Association Task (DAT) for creativity, the Watson–Glaser Critical Thinking Appraisal for critical thinking, and the FourSight framework for problem-solving. Learning agility was measured using a multidimensional behavioral scale. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that higher-order cognitive abilities play a more prominent role in shaping learning agility than basic cognitive abilities. Creativity and problem solving consistently demonstrate significant positive relationships with learning agility across organizational contexts, while reasoning, critical thinking, and perception show context-dependent effects across organizational environments. These findings suggest that learning agility is primarily driven by generative and evaluative cognitive processes rather than by basic cognitive efficiency alone. The study contributes to a deeper understanding of the cognitive architecture of learning agility and provides insights for organizations seeking to develop adaptive talent in rapidly evolving technological environments. 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

Crisis management has evolved from a reactive organizational function into a strategic capability grounded in organizational learning, knowledge-based processes, and behavioral alignment, thereby enhancing institutional resilience in volatile environments. This study examines how organizational and financial determinants contribute to crisis management success in the United Arab Emirates (UAE). It integrates crisis management culture as a learning-oriented mediating capability. It incorporates a Theory of Planned Behavior (TPB)-based behavioral extension to explain how attitude, subjective norms, and perceived behavioral control shape intention toward crisis-related compliance. Using SPSS regression analysis and Partial Least Squares Structural Equation Modeling (PLS-SEM), the findings indicate that policies, procedures, and financial stability exert significant positive effects on crisis management success, whereas trained human resources show no direct significant impact. Crisis management culture emerges as a key mediating mechanism that enables knowledge integration, supports organizational learning processes, and translates structural preparedness into coordinated action. The TPB-based extension further shows that attitude, subjective norms, and perceived behavioral control significantly predict intention, and that intention is positively associated with crisis management success. The results suggest that effective crisis governance depends not only on formal structures and financial resources but also on learning-oriented cultures and behavioral mechanisms that transform institutional knowledge into coordinated crisis responses. Full article

This study investigates the factors influencing customer engagement in AI-powered fitness applications and the subsequent impact on behavioral outcomes such as word of mouth and sustainable consumption. A quantitative research design was employed, with data collected through a structured survey from users of AI fitness applications, and analyzed using Structural Equation Modeling (SEM). Drawing on the Information Systems Success Model and engagement theory, the research examines the roles of service quality, system quality, information quality, health consciousness, anthropomorphism, and personal innovativeness. Findings reveal that higher perceived quality across service, system, and information dimensions, coupled with health consciousness and human-like features, significantly enhances user engagement. Engagement, in turn, drives both advocacy and sustainable behaviors, while personal innovativeness selectively amplifies the effect of system quality. The study advances theoretical understanding by adapting and extending established models to the context of AI-driven health technologies, while also providing practical insights for the development of intelligent, user-centric fitness applications that promote sustained engagement and responsible use. Full article

Rapid urbanization and population growth have intensified solid waste management (SWM) challenges in developing countries, where institutional capacity and stakeholder participation remain limited. Existing studies, particularly in the context of Pakistan, largely examine isolated technical or environmental aspects, with limited integration of sustainability dimensions and stakeholder dynamics. This study develops and empirically validates an integrated structural equation modeling (SEM) framework to examine the interrelationships among sustainable solid waste management systems (SSWM), stakeholder engagement (SE), and solid waste management strategies (SWMS). Primary data were collected from 420 stakeholders representing diverse groups. The measurement model demonstrated strong reliability and validity, while the structural model exhibited excellent fit indices. Results indicate that economic, social, technical and environmental and institutional dimensions significantly shape SSWM. Structural path analysis reveals that SSWM significantly influences SE and SWMS, while SE has a significant effect on SWMS. Mediation analysis confirms that SE partially mediates the relationship between SSWM and SWMS, highlighting the critical role of participatory governance. The findings demonstrate that achieving sustainable waste management requires the integration of system-level capacity, stakeholder engagement, and strategic implementation. This study contributes to the sustainability literature by providing a holistic framework and providing understanding for policymakers to promote circular economy practices and resource efficiency in developing countries. 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

Purpose: This study investigates the mediating role of internal marketing (IM) in the relationship between artificial intelligence (AI) applications and quality of work life (QWL). Methodology: A quantitative cross-sectional research design was employed. Data were collected via self-administered questionnaires from a sample of 418 employees across service ministries in Saudi Arabia and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) as the analytical instrument. Findings: The results reveal that the direct association between AI applications and QWL was not statistically significant. However, a significant indirect relationship was established, indicating that the effect operates entirely through IM. Specifically, AI applications are positively associated with IM practices, which in turn strongly predict higher QWL in the tested model. Originality/Contributions: The study advances current literature by empirically validating IM as the critical organizational mechanism required to translate AI deployment into employee well-being within public-sector institutions. Practical Implications: Decision-makers must couple AI adoption with targeted IM strategies—such as continuous training, job empowerment, and effective internal communication—to ensure a sustainable, human-centered digital transformation. Full article

This study examines the role of circular services in generating economic value within the construction sector, focusing on firms belonging to the Sustainable Habitat Cluster in the Aburrá Valley, Colombia. The research analyzes how circular business model strengthening translates into economic outcomes through the implementation of circular service portfolios. Using a Partial Least Squares Structural Equation Modeling (PLS-SEM) approach, the study evaluates the relationships between circular business model capabilities, circular service implementation, and circular revenue generation. The results confirm a sequential mechanism linking strategic capabilities to economic outcomes, where strengthening circular business models significantly enhances the implementation of circular services, which in turn strongly predicts the generation of circular revenues. The findings indicate that circular strategic orientation is a necessary but insufficient condition for economic value creation, as monetization occurs only when circular principles are translated into concrete service offerings. The study highlights the central role of circular services as the operational bridge between strategic readiness and economic performance, contributing to the literature on circular business models and Product–Service Systems (PSS) by providing empirical evidence of how circular strategies translate into revenue generation within the built-environment sector. Full article

Tourism destination marketers increasingly rely on video advertising, yet the psychological mechanisms linking perceived advertising design and destination familiarity to engagement remain underspecified in tourism contexts. Drawing on narrative transportation and advertising stimulation perspectives, this study examines how perceived advertising design and destination familiarity relate to narrative transportation and advertising stimulation, and how these mechanisms relate to engagement. Using a survey of 915 Portuguese respondents and structural equation modeling in AMOS, we estimate a model comprising advertising design, destination familiarity, narrative transportation, advertising stimulation, and engagement. Results show that perceived advertising design is positively associated with narrative transportation (β = 0.451, p < 0.01) and advertising stimulation (β = 0.158, p < 0.01). Destination familiarity is also positively associated with narrative transportation (β = 0.215, p < 0.01) and advertising stimulation (β = 0.104, p < 0.01). Narrative transportation is strongly associated with advertising stimulation (β = 0.659, p < 0.01), whereas narrative transportation does not show a significant direct association with engagement (β = 0.086, n.s.). Advertising stimulation is positively associated with engagement (β = 0.288, p < 0.01). Findings suggest that, in this context, affective activation (stimulation) may be a more proximal correlate of self-reported engagement than narrative immersion alone, warranting careful interpretation given the cross-sectional, self-report design. Full article

Radiation use efficiency (RUE) is closely associated with cotton biomass and yield, yet the synergistic regulation of phenotypic structure and physiological potential remains unclear. A field experiment (2024–2025) in Anyang, China, utilized three independent trials: six sowing dates (from 12 April to 12 May at 6-day intervals, S1–S6), six planting densities (1.5, 3.3, 5.1, 6.9, 8.7, and 10.5 × 10⁴ plants·ha⁻¹, D1–D6), and ten cultivars with distinct architectures (V1–V10). Feature importance and structural relationships were quantified via random forest (RF) and partial least squares structural equation modeling (PLS-SEM). Results indicated that delaying sowing reduced true leaf number (TLN) and plant height (PH), with the April 24 sowing (S3) optimizing leaf area index (LAI, 2.57) and light interception rate (iPAR, 0.61). Increasing density significantly enhanced population-level LAI, above-ground biomass, and RUE, despite a progressive decline in TLN. Among cultivars, CCRI 60 (V6) exhibited superior structural traits (PH: 72.94 cm; iPAR: 0.61), while CCRI 113 (V8) exhibited the highest maximum carboxylation rate (V_cmax, 88.9 μmol·m⁻²·s⁻¹) and RUE (4.88 g·MJ⁻¹). Across the comprehensive dataset (integrating the density, sowing date, and cultivar trials), iPAR exhibited the highest relative importance (42.01%) for RUE variation, while associated structural traits (PH, LAI, TLN) yielded a cumulative relative importance of 41.69%. RUE was strongly associated with biomass accumulation (path coefficient > 0.97), which subsequently optimized yield components. Conversely, within the cultivar-comparison subset, the relative importance of iPAR decreased to 17.95%, while V_cmax rose significantly to 19.20%. PLS-SEM indicated that canopy structure exerted a significant negative association with photosynthetic potential (V_cmax, J_max) within this cultivar subset (path coefficient ≈ −0.51), whereas enhanced physiological potential was positively associated with resource allocation to yield components (path coefficient ≈ 0.57). Consequently, mitigating the inherent trade-off between canopy structure and leaf photosynthetic capacity is critical for further improving RUE and cotton yield under similar production environments. Full article

Construction management, from the contractor’s perspective, is led by the Construction Manager (CM). The work motivation and leadership style of the CM are critical variables for the successful execution of construction projects. The scientific literature identifies participative leadership as the most effective style for mitigating conflicts among various stakeholders. However, analyzing the specific variables that influence a CM’s conflict resolution capacity remains an underexplored area. Furthermore, while the CM must act as a leader for their team (subcontractors, suppliers, etc.), they remain accountable to the contractor’s senior management. Therefore, this study aims to analyze the mediating role of CM motivation in the relationship between leadership and conflict resolution capacity using Partial Least Squares Structural Equation Modeling (PLS-SEM). In the construction industry, conflict resolution is not merely a situational fix but a critical process of capturing and externalizing tacit knowledge. Knowledge management and the ability to resolve conflicts in the construction sector are directly linked, critical, and strategic in nature. Construction is an industry characterized by fragmentation, the temporary nature of its projects, diversity of stakeholders (developers, builders, subcontractors, engineering firms) and a high level of uncertainty. In this environment, conflict is virtually inevitable. However, the way in which a CM handles a conflict determines whether it becomes a destructive dispute or an opportunity for improvement. Full article

This study discusses the influence of Digital Leadership (DL) on Sustainable Innovation Performance (SIP) in telecommunications companies. In addition to examining the direct effect of Digital Leadership, the study focuses on the mediating roles of Knowledge Sharing (KS) and Employee Engagement (EE). A sample of 412 employees was collected by a simple cross-sectional survey. A partial least squares structural equation modeling (PLS-SEM) approach was used for analyzing results. The study reveals that Digital Leadership directly and positively enhanced Knowledge Sharing but did not lead to a significant direct influence on Employee Engagement and Sustainable Innovation Performance. Moreover, Knowledge Sharing did not significantly influencing Sustainable Innovation Performance, a condition that was the strongest predictor of Sustainable Innovation Performance emerging from Employee Engagement. The mediation analysis shows that neither Knowledge Sharing nor Employee Engagement mediates the relationship between Digital Leadership and Sustainable Innovation Performance. The objective contribution of this study is to shed light on the idea that Digital Leadership and Sustainable Innovation Performance are not directly related but may instead reflect other circumstances or contextual conditions. The research offers practice advice in showing that Employee Engagement benefits organizational sustainable innovation results by urging companies to consider not only Digital Leadership strategies but also alternative strategies that foster employee involvement. Full article

The study examines the relationship between Corporate Social Responsibility (CSR) adoption and firms’ future CSR investment, with a particular focus on the mechanisms and conditions that shape this relationship, drawing on the business case perspective and the resource-based view. A quantitative research design was employed using survey data collected from 568 business executives in Greece. Structural Equation Modeling (SEM) was applied to test the proposed relationships. The findings indicate that CSR adoption has a significant positive impact on future CSR investment, confirming that CSR engagement evolves into a sustained strategic commitment. Perceived benefits are found to play significant mediating roles, suggesting that firms increase future CSR investment when they recognize the value generated by CSR. In contrast, institutional barriers negatively moderate this relationship, weakening the effect of CSR adoption. The study demonstrates that the continuation of CSR investment is driven by internal reinforcement mechanisms and external conditions rather than purely by financial constraints. It offers empirical evidence that CSR adoption initiates a self-reinforcing process supported by perceived value decisions. The findings provide practical insights, emphasizing the importance of strengthening institutional frameworks and enhancing the perceived benefits of CSR to foster long-term investment in sustainable business practices. Full article