Search Results (2,293)

Fashion live commerce has rapidly emerged as a compelling format that blends entertainment, real-time interaction, and product promotion. However, limited research has examined how specific experiential and perceptual factors influence consumer behavior in this context. This study aims to identify the key psychological and environmental drivers of satisfaction, continued platform use, and purchase intention among viewers of fashion live commerce. Using the stimulus–organism–response framework, this research focuses on the effects of perceived credibility, social media influencer characteristics, informativeness, internal shop environment, and monetary savings. Data were collected from 300 users of fashion live commerce platforms and analyzed using partial least squares structural equation modeling (PLS-SEM). The results indicate that all predictor variables significantly influence either satisfaction or current use, and both satisfaction and current use significantly predict purchase intention. Among the factors, satisfaction plays a central role, acting as a strong predictor for both current engagement and future buying decisions. These findings offer theoretical insights into consumer engagement in live commerce and provide practical guidance for streamers, marketers, and platform designers aiming to improve user experience and conversion rates. This study contributes to understanding the evolving dynamics of digital shopping environments shaped by social and emotional interactions. Full article

The rapid development of autonomous driving technology has been a key driver for the emergence of driverless delivery vehicles. To promote wider adoption, it is essential to address consumers’ concerns about safety and reliability, leverage psychological factors, and implement supportive policies that encourage technology adoption while ensuring public safety and privacy. Therefore, it is necessary to explain and predict consumers’ behavior and intention to adopt driverless delivery vehicles. To this end, this study extends the Technology Acceptance Model (TAM) to include technological complexity and perceived trust. This study evaluates the model by applying necessary condition analysis (NCA) and partial least squares structural equation modeling (PLS-SEM) to analyze data from 579 respondents from Jiangsu Province, China. This study explores the sustainability implications of autonomous delivery vehicles, highlighting their potential to reduce environmental impact and promote a more sustainable transportation system. The outcomes indicate that perceived ease of use (PEU), attitude, perceived trust, technological complexity (TECOM), and perceived usefulness (PU) are significant determinants and necessary conditions of consumers’ intention to adopt driverless delivery vehicles. Perceived trust and TECOM had a significant and indirect influence on consumers’ intention to adopt driverless delivery vehicles via PU and PEU. Perceived trust and technological complexity had a substantial impact on consumers’ adoption intention of driverless delivery vehicles. The study recommends that managers work closely with regulators to ensure their technologies meet all local standards and regulations. It also recommends its potential to reduce carbon emissions, improve energy efficiency, and contribute to a more sustainable transportation system. Full article

Ionic liquids (ILs) can ideally reduce defects and improve the film stability of emissive metal halide perovskite films. In this work, we measure how the structure and emission of methylammonium lead tribromide (MAPbBr₃) perovskite films is modulated by long alkyl chain-containing pyridinium, imidazolium, or pyrrolidinium ILs. Two different film deposition methods are compared, with the resultant films characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), and photoluminescence (PL) spectroscopy. For the latter, the differences in PL intensity of the perovskite are quantified using photoluminescence quantum efficiency (PLQE) measurements. It is found that a spin coating method in conjunction with the use of an imidazolium-containing IL (for a given precursor concentration) produces the strongest emissive perovskite. This optimal enhancement is attributed to a function of accessible surface charges associated with the heterocyclic cation of a given IL and perovskite defect passivation by bromide, the latter elucidated with the help of density functional theory. Proof-of-concept device fabrication is demonstrated for the case of a light emitting diode (LED) with the IL present in the emissive perovskite layer. Full article

This study examines the effect of internal dynamic capabilities i.e., digital leadership, environmental awareness, and organizational learning, on sustainable supply chain performance as studied in the logistics sector. It builds on the Dynamic Capabilities Theory by combining notions of green innovation and sustainability and fills the growing gap in the existing literature. Despite the fact that these domains have been extensively studied independently, there has been limited research examining how internal capabilities contribute to green supply chain innovation (GSCI) that in turn results in sustainability outcomes, especially in the case of emerging markets. Seven hypotheses were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM) analysis of data collected from 312 logistics and supply chain professionals in Jordan. This study shows that each of the three capabilities has a major effect on GSCI and therefore sustainable performance. Linking the most influential predictor of sustainability outcome to sustainable supply chain performance, as indicated by the strongest effect (β = 0.825, p < 0.001) between GSCI and sustainable supply chain performance, and followed by significant coefficients between the sustainable information processing (β = 0.261, p < 0.01), and information capabilities (β = 0.297, p < 0.001), indicates that the theory is more suited to GSCI. In particular, digital leadership had the largest impact on the green innovation (β = 0.481, p < 0.001), indicating that the role of digitally driven leadership is to facilitate eco-innovation. In addition, this intermediate factor, GSCI, serves as a variable that mediates relationships between the capabilities and the sustainability outcomes. As the results here suggest, leveraging internal capabilities is a very tangible channel for green innovation that has important ramifications for practitioners and policymakers facing resource constraints. Full article

(1) Background: This paper examines the relationships between generational handover protocols, knowledge transfer behavior, and key organizational outcomes. (2) Methods: A quantitative design was applied, using non-parametric tests and partial least squares structural equation modeling (PLS-SEM) on survey data from 168 employees in companies located in the Basque Country. (3) Results: The presence of formal knowledge transfer protocols and generational handover processes was significantly associated with greater employee knowledge-tranfer behaviors. These behaviors, in turn, had significant positive effects on organizational innovation and job performance. Although moderate correlations were observed with strategy, performance, and competitive advantage, the structural model did not confirm direct relationships. (4) Conclusions: Despite their strategic importance, many organizations still lack formalized mechanisms for knowledge preservation. This study offers a framework for understanding the impact of structured knowledge transfer practices on organizational performance and suggests avenues for future research in knowledge continuity and succession planning. Full article

The COVID-19 pandemic has amplified concerns about healthcare access, particularly among vulnerable populations. This study extends Andersen’s behavioral model to investigate how fear of high-risk locations, alongside predisposing, enabling, and need factors, shapes healthcare-seeking behavior in Penang, Malaysia. A survey of 211 individuals (58% response rate) was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results reveal that need factors—specifically self-rated health and chronic illness—strongly predict healthcare utilization. However, this relationship is moderated by fear of infection, leading some high-risk individuals to forgo care despite medical necessity. Enabling factors, including financial resources and access to public healthcare, showed limited influence, likely due to Malaysia’s universal healthcare system and growing use of telemedicine. Older adults maintained healthcare utilization among predisposing variables, while higher-educated individuals were more cautious, possibly due to heightened health literacy and trust in digital alternatives. Although fear influenced care-seeking behavior for minor ailments, it did not significantly deter individuals from accessing services for severe conditions. These findings underscore the nuanced interaction between psychosocial factors and institutional context in shaping healthcare decisions during health crises. Full article

Background: The mediating effect of business resilience in the association between digital logistics strategy and competitive advantage is investigated in emerging markets. Given current global events, digital logistics is more than merely a competitive advantage for firms looking for stability and sustainability. Based on the Resource-Based View (RBV), the research aims to explore how digital strategies promote resilience and performance outcomes, particularly for SMEs in turbulent environments. Methods: They used mixed methods. The quantitative data were obtained from 227 Jordanian SMEs using a structured survey, and the qualitative data were from 10 semi-structured interviews with experts in logistics and marketing. Hypothesized relationships were tested through Partial Least Squares-Structural Equation Modeling (PLS-SEM) and qualitative validation through Thematic Analysis. Results: The results reveal that business resilience is a potent mediator between digital logistics strategies and competitive advantage. Both content marketing and social media marketing contribute to the enhancement of sustainable performance and to decreasing levels of market volatility. Email also has an impact on the sustainability, but does not directly or indirectly affect the volatility. Sustainable performance is thus confirmed to be a major factor for market stability. Conclusions: The findings emphasize the need for resilience-based digital logistics strategies for SMEs in developing economies. Well-directed content and social media marketing support both sustainability and competitive advantage. These findings offer managerial implications for the development of adaptive capacities to achieve long-term performance objectives in uncertain environments. Full article

This study explores the employability of engineers in the context of Industry 4.0, focusing on the KASH model (Knowledge, Attitude, Skills, Habits). Using a sequential exploratory design, we collected data from 800 engineers in Morocco through an online questionnaire. The findings reveal that attitude and knowledge have a significant impact on employability, whereas skills and habits show moderate to weak effects. The study employs Partial L6east Squares (PLS) Structural Equation Modeling to validate the model, demonstrating a strong predictive relevance (Q² = 0.714) and a high coefficient of determination (R² = 0.716). The results suggest that engineering schools should emphasize attitude and knowledge development to enhance employability in the rapidly evolving job market of Industry 4.0. Full article

This study assesses the performance impact of lean construction practices in Engineering, Procurement, and Construction (EPC) projects in China. While lean methods have demonstrated substantial benefits in conventional construction, their implementation in the EPC context—characterized by higher complexity and integration—remains underexplored, particularly within the Chinese infrastructure sector. This research develops a structured framework that classifies lean practices into five functional categories: planning and scheduling (PS), process and workflow optimization (PWO), quality and safety enhancement (QSE), resource and maintenance (RM), and visualization and communication (VC). This study evaluates the influence of these practices on four key performance indicators: efficiency and resource management, quality and safety, stakeholder satisfaction, and organizational and market impact. Data were collected from 456 EPC stakeholders via a structured questionnaire and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that PS, PWO, and QSE exert the strongest positive effects on performance, while RM and VC contribute in more context-specific ways. The results highlight the value of lean practices for improving operational performance, stakeholder engagement, and sustainability in complex project delivery systems and underscore the need for policy support and digital integration to enhance lean adoption in Chinese EPC sector. Full article

A company’s competitive advantage largely depends on the longevity and quality of its customer relationships, making it essential to understand which tools best support these interactions. In particular, identifying the factors that shape the impact of Customer Relationship Management (CRM) systems on business performance is crucial. This study examines the influence of CRM on the business performance of Portuguese companies by employing a conceptual model structured around five dimensions: customer-centric management (CCM), CRM organization (CRMO), operational CRM (OCRM), customer service quality (CSQ), and technological turbulence (TT). Data were gathered via a questionnaire completed by employees of Portuguese firms using CRM systems, yielding a total of 228 valid responses. Of the nine hypotheses tested, eight were confirmed. The results indicate that CRM organization (CRMO) exerts the strongest positive influence on business performance (0.457), followed by customer service quality (CSQ), operational CRM (OCRM), and customer-centric management (CCM). The study also confirms that technological turbulence (TT) moderates the relationship between the CRM dimensions and business performance. These findings suggest that the proposed model is well-suited to the context of Portuguese SMEs and provide valuable insights for managers aiming to enhance competitiveness through the strategic use of CRM systems. Additionally, the results offer a relevant contribution to the academic literature on CRM and business performance. Full article

This paper examines the impacts of AI-powered assistive technologies (AIATs) on the academic success of higher education university students with visual impairments. As digital learning contexts become progressively more prevalent in higher education institutions, it is critical to understand how these technologies foster the academic success of university students with blindness or low vision. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model, the study conducted a quantitative research approach and collected data from 390 visually impaired students who were enrolled in different universities across Saudi Arabia (SA). Employing Partial Least Squares Structural Equation Modeling (PLS-SEM), the paper tested the influences of four UTAUT dimensions—Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), and Facilitating Conditions (FC)—on Academic Performance (AP), while also evaluating the mediating role of Behavioral Intention (BI). The results revealed a significant positive relationship between the implementation of AI-based assistive tools and students’ academic success. Particularly, BI emerged as a key mediator in these intersections. The results indicated that PE (β = 0.137, R² = 0.745), SI (β = 0.070, R² = 0.745), and BI (β = 0.792, R² = 0.745) significantly affected AP. In contrast, EE (β = −0.041, R² = 0.745) and FC (β = −0.004, R² = 0.745) did not have a significant effect on AP. Concerning predictors of BI, PE (β = 0.412, R² = 0.317), SI (β = 0.462, R² = 0.317), and EE (β = 0.139, R² = 0.317) were all positively associated with BI. However, FC had a significant negative association with BI (β = −0.194, R² = 0.317). Additionally, the analysis revealed that EE, SI, and PE can all indirectly enhance Academic Performance by influencing BI. The findings provide practical insights for higher education policymakers, higher education administrators, and AI designers, emphasizing the need to improve the accessibility and usability of sustainable and long-term assistive technologies to better accommodate learners with visual impairments in higher education contexts. Full article

Blockchain technology is reshaping the sports industry by enhancing transparency, data security, and fan engagement through applications such as smart contracts, tokenized sponsorships, and decentralized ticketing. This study investigates blockchain adoption in Romanian team sports, specifically football and basketball, through a comparative analysis based on a survey of 293 sports professionals (213 from football and 80 from basketball). Using structural equation modeling (SEM) with SmartPLS and cluster analysis in SPSS, the study explores the perceived benefits of blockchain and its relationship with athlete performance. The findings reveal distinct adoption patterns: football shows higher use of blockchain in ticketing and fan engagement, while basketball leads in performance analytics and financial support mechanisms. Statistically significant differences were confirmed through MANOVA, and clustering revealed varied stakeholder perceptions across professional roles. Benchmarking against sectors like finance and healthcare highlights transferable best practices for blockchain integration in sports. Full article

Sharing is an important part of an organization’s culture, consisting of learning, innovation, and performance through the promotion of expertise, ideas, and best practices among employees. This study aimed to analyze the relationships between transactional leadership, human capital, and knowledge sharing. This study used a quantitative approach by using 355 responses from employees who work at customs offices throughout Sulaymaniyah Governorate, located in the Kurdistan region of Iraq. PLS (SEM) was used as a method of estimation in the study to test the hypotheses. The findings show that although transactional leadership greatly improves the development of human capital, it does not directly affect knowledge sharing. Moreover, knowledge and experience engaging in activities involving knowledge sharing and participating in human capital are quite important. The findings also show that the increase in human capital corresponds to the degree of effectiveness of leadership in knowledge management. Therefore, the findings provide practical implications for companies to increase employee capacities by improving transactional leadership within organizations. Full article

Corporate sustainability has emerged as a critical imperative for firms navigating volatile markets and ecological constraints, yet the mechanisms linking organizational practices to sustainability outcomes remain underexplored, particularly in developing economies. Drawing on the resource-based view and dynamic capabilities theory, this paper examines how transformational leadership and knowledge sharing synergistically enhance innovation capability, which in turn fosters environmental dynamism and corporate sustainability performance. Using a structured questionnaire within a cross-sectional design to gather data from 140 Moroccan SMEs, data were collected via an online questionnaire from 140 Moroccan SME owners and managers, with hypotheses tested using partial least squares structural equation modeling (PLS-SEM). The results show that knowledge sharing, and transformational leadership significantly strengthen innovation capability. Innovation capability further drives environmental dynamism, which positively impacts sustainability performance. These findings advance theory by integrating knowledge-based, leadership, and dynamic capability perspectives into a novel pathway for achieving sustainability goals. The study underscores the necessity for SMEs in developing nations to cultivate leadership that inspires knowledge exchange and adaptive innovation, enabling resilience amid ecological and market shifts. By highlighting these internal drivers, the research offers actionable insights for SMEs and policymakers seeking to align business innovation strategies with sustainability objectives and pro-environmental transformation in line with the UN Sustainable Development Goals (SDGs). Full article

With the emergence of AI technology, its adoption in higher education has become an interesting field for researchers. The present study explores the acceptance of AI for learning the English language by Pakistani EFL students using the UTAUT-2 and Metacognition theory. The UTAUT-2 questionnaire was adapted with minor changes to make it suitable for the EFL context. Data were collected from the English departments of the top ten general universities in Pakistan to make the findings generalizable. Another step taken to ensure generalizability was the sampling of 611 students randomly from both undergraduate (BS and ADP) and postgraduate (MPhil and PhD) programs studying in different semesters. PLS-SEM was employed for data analysis. In the first step, the PLS algorithm was run for the measurement model, which confirmed the reliability, validity, and fitness of the model. Second, the bootstrapping method was used for hypothesis testing. The findings reveal that six of the ten hypotheses for direct relationships are supported. Habit (0.489) was found to be the strongest contributor to BI, followed by PE (0.141), SI (0.100), and FC (0.093). Moreover, actual use behaviour was predicted by habit (0.325) instead of BI and FC. These findings are supported by metacognition theory, as the habit of AI seems to shape the metacognitive knowledge of EFL learners in place of traditional learning methods, and other factors seem to reinforce the metacognitive experience of using AI language. The study suggests implications for EFL experts, academia, and policymakers to strategically integrate AI into language learning by informing them of its potential benefits and risks. Full article