Purpose This study investigates a research model linking resource mobilisation (RM), management commitment to quality (MCQ), digital supply chain adoption (DSCA) and operational performance (OP) under the moderating role of digital maturity (DM). Design/methodology/approach Data were gathered using an online questionnaire distributed to a sample of Moroccan manufacturing firms. A total of 130 valid questionnaires were analysed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Findings The results indicate that RM influences MCQ significantly, which in turn affects DSCA, leading to a positive impact on OP. In addition, the findings reveal that DM lessens the strength of the relationship between DSCA and OP, suggesting that the more digitally mature the organisations the more the risk of rigidity integration with operational gains. These findings provide nuanced insights into the mechanisms and effects of DSCA. Originality/value This study contributes to literature on DSCA by testing a model that links digitalisation's resources, MCQ and DM. The findings offer actionable guidance for managers. They clarify the role of MCQ in achieving positive effects on DSCA and operational gains while also warning against the threats of rigidity stemming from DM.

This study addresses a critical gap in understanding how teacher innovation drives the utilization of digital resources in education, mediated by teachers' self-efficacy and collaboration, and moderated by professional development. Using data from 68,054 teachers across 81 countries in the PISA 2022 teacher questionnaire, we retained an analytic sample of 64,852 teachers after applying inclusion criteria and listwise deletion of missing values. We employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze these relationships. Results reveal that teacher innovation significantly predicts digital resource usage, with self-efficacy and collaboration serving as key mediators. Professional development amplifies these relationships. This study offers novel insights into the mechanisms linking teacher attributes to digital resource adoption, providing actionable strategies for policymakers to enhance educational digitalization. This study moves beyond the conventional individual-centered perspective of the technology acceptance model, offering a comprehensive and systematic strategy to support the digital transformation of education.

This study aims to analyze the effect of training quality on the performance of investigators at the Directorate of General Criminal Investigation (Ditreskrimum) of the Lampung Regional Police, with competency as a mediating variable. The study is motivated by the need to enhance investigator professionalism in response to the increasing complexity of criminal cases and rapid technological developments. This research employs a quantitative approach with a causal research design. The population consists of all 54 investigators at Ditreskrimum Polda Lampung, who were included as the sample using a saturated sampling technique. Data were collected through Likert-scale questionnaires and analyzed using Structural Equation Modeling (SEM) based on Partial Least Squares (PLS). The results indicate that training quality has a positive and significant effect on investigator competency and performance. Competency also has a positive and significant effect on investigator performance. Furthermore, competency is proven to significantly mediate the effect of training quality on investigator performance.

Purpose Generative artificial intelligence (GenAI) has been widely used in businesses; however, limited empirical research examines how work-related GenAI use (WRGAIU) influences human resource (HR) effectiveness and learning mechanisms. This study aims to fill this gap by investigating the direct influence of WRGAIU on HR effectiveness as well as on explorative and exploitative learning. Further, this study also examines whether two learning mechanisms mediate the relationship between WRGAIU and HR effectiveness. This study also examines the moderating role of market turbulence in those direct and indirect relationships, uncovering new insights on how GenAI can ignite HR outcomes under dynamic circumstances. Design/methodology/approach Survey data from 314 HR employees working at British private companies were collected using the online platform Prolific Academic. We used Partial Least Squares-based Structural Equation Modelling to test the hypotheses. Findings The results reveal that WRGAIU directly influences HR effectiveness, explorative learning and exploitative learning. However, the learning mechanisms were found to have no mediating role in the relationship between WRGAIU and HR effectiveness. Moreover, results show that when employees use work-related GenAI, market turbulence becomes insignificant for them. Practical implications The study uncovers how WRGAIU can be instrumental in igniting HR effectiveness and learning mechanisms among HR employees, regardless of market turbulence. Originality/value The results suggest that WRGAIU should be developed in organisations to achieve multiple outcomes, especially in developing HR effectiveness and explorative and exploitative learning of employees to keep organisations protected from external market factors, i.e., market turbulence.

This study aims to analyze the influence of social media marketing, influencer endorsements, and price discounts on impulsive purchases with trust as a mediating variable in Bohe Bali perfume consumers. This study uses a quantitative approach with a survey method. Data were collected through questionnaires distributed to Bohe Bali consumers and analyzed using the Partial Least Square (PLS) method. The results showed that social media marketing did not have a significant direct effect on impulsive purchases, but had a positive and significant effect on trust. Conversely, influencer endorsements and price discounts were proven to have a positive and significant direct effect on impulsive purchases. Price discounts were the variable with the strongest direct effect in encouraging impulsive purchases. Furthermore, influencer endorsements and price discounts did not have a significant effect on trust. The test results also showed that trust had a positive and significant effect on impulsive purchases. In testing the mediation effect, trust was proven to fully mediate the influence of social media marketing on impulsive purchases. However, trust was unable to mediate the influence of influencer endorsements and price discounts on impulsive purchases. These findings indicate that social media marketing works through building trust, while influencer endorsements and price discounts encourage impulse purchases through emotional mechanisms and price urgency. The conclusion of this study shows that trust is a key factor in bridging digital marketing strategies with impulse buying behavior, especially for perfume products that are experience goods. Therefore, Bohe Bali needs to balance short-term promotional strategies with efforts to build consumer trust sustainably.

Purpose: This study examines the association between digital forensic capabilities and fraud detection effectiveness in Nigeria’s five largest deposit money banks—United Bank for Africa Plc, Zenith Bank Plc, Access Bank Plc, First Bank Nigeria Limited, and Guaranty Trust Bank Plc. Specifically, it evaluates the relative contributions of network forensics, cloud forensics, mobile forensics, and Internet of Things (IoT) forensics to fraud detection effectiveness. Methodology: A cross-sectional survey design was adopted, with data collected through structured questionnaires administered to staff of the selected banks. Of the 306 questionnaires distributed, 243 valid responses were obtained, representing a 79% response rate. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to test hypothesized relationships and Artificial Neural Network (ANN) analysis to assess predictive importance. PLS-SEM analysis was conducted using JASP version 0.95.3, while ANN estimation employed a multilayer perceptron model in SPSS version 27. Results and conclusion: The PLS-SEM results indicate that digital forensic capabilities jointly explain a substantial proportion of variance in fraud detection effectiveness with all R² > 0.75. Cloud forensics (β = 0.515) and network forensics (β = 0.500) exhibit the strongest associations, followed by IoT forensics (β = 0.456) and mobile forensics (β = 0.449). ANN results corroborate these findings, ranking cloud forensics as the most important predictor (normalized importance = 100%), closely followed by network forensics (99.7%), mobile forensics (85.3%), and IoT forensics (79.8%). Implication of findings: The study implies that bank management should prioritize investment in cloud and network forensic infrastructures, complemented by targeted training and process integration, to enhance fraud detection performance. However, the cross-sectional and self-reported nature of the data limits causal inference, indicating the need for future longitudinal studies using objective fraud performance indicators.

In the context of periodic motor vehicle testing, this study investigated the relationship between service quality and officer work discipline on public awareness and compliance. This study is based on the fact that the level of public compliance is still low and there is a difference between operational practices and operational standards at the Motor Vehicle Testing Management Unit (UPPKB) Ujung Menteng, DKI Jakarta. This study uses a quantitative and survey approach. Structural Equation Modeling (SEM) with Partial Least Squares (PLS)-based variants was used to analyze data collected from questionnaires given to 170 service users. The results showed that service quality and work discipline significantly affected public awareness, but neither directly affected compliance. There is evidence that public awareness is a fully mediating factor, or full mediation, that significantly influences compliance and is an indirect pathway to work discipline and quality of service. These results show that service strategies should focus on improving technical procedures and education to raise awareness as the key to improving sustainable compliance

Purpose of the study: This study investigates the transformative role of Meaning Reconstruction (MR) in mediating the relationship between Post-Purchase Dissonance (PPD) and Eudaimonic Well-Being (EWB) in the context of digital education service consumption in Indonesia. Methodology: This study employs a quantitative explanatory design using Structural Equation Modeling–Partial Least Squares (SEM-PLS). Data were collected through web scraping from 500 publicly accessible posts on Twitter (X), Reddit, and TikTok discussing post-purchase experiences with digital education services in Indonesia (2020–2024). Computational text analysis using a fine-tuned IndoBERT model was applied to derive construct scores for PPD (X1–X3), MR (M1–M4), and EWB (Y1–Y4). Indicators were quantified using algorithmically normalized NLP-based semantic intensity scores ranging from 1 to 7, representing computational estimations of construct magnitude rather than self-reported NLP-based normalized semantic score (1–7) responses. Main Findings: Results confirm that PPD significantly influences MR (β=0.446, p<0.001) and MR strongly predicts EWB (β=0.481, p<0.001). The direct path PPD→EWB is significant (β=0.176, p<0.001), while the indirect effect via MR is also significant (β=0.214, t=8.248, p<0.001), with a Variance Accounted For (VAF) of 54.8%, indicating partial mediation. R²(MR)=0.199 and R²(EWB)=0.338. All measurement model criteria are satisfied: outer loadings >0.70, AVE >0.50, CR >0.70, and HTMT <0.85. Novelty/Originality of this study: Reconstruction as a critical transformative mechanism, reframing post-purchase dissonance from a purely negative outcome into a catalyst for consumer psychological growth. The use of computational text analysis (NLP + web scraping) as an alternative to conventional surveys further contributes methodological novelty.

Purpose A quantitative research design was adopted using a Web-based survey targeting 290 Indian procurement experts across public and private sectors. The data were analyzed using SmartPLS 4.0, applying the Partial Least Squares–Structural Equation Modeling technique to test measurement reliability, structural relationships and moderating effects. Design/methodology/approach This study investigates the role of Big Data Analytical Capabilities (BDAC) in enhancing firms’ environmental, social and governance (ESG) performance, with a particular emphasis on the moderating effect of Green Finance (GF). It aims to uncover how data-driven capabilities and sustainable financial mechanisms jointly promote ESG outcomes among Indian procurement professionals. Findings The results reveal that BDAC significantly and positively influences all ESG dimensions, particularly Environmental Performance (EP) and Green Performance (GP). Although GF independently improves ESG outcomes, its effect is weaker than BDAC’s. Importantly, GF significantly moderates the relationship between BDAC and GP, but not with EP or Social Performance, highlighting a synergistic role in advancing environmentally driven outcomes. Practical implications The findings underscore that firms can strengthen ESG performance by simultaneously investing in big data analytics and green financing instruments. Managers and policymakers should encourage data-driven sustainability monitoring and facilitate access to green funds to support environmentally responsible procurement and corporate governance practices. Originality/value This study extends the Resource-Based View Natural Resource-Based View and Resource-Dependence Theory by integrating technological and financial resources as complementary drivers of sustainability. To the best of the authors’ knowledge, this study is among the first to empirically examine this interaction in the context of Indian procurement experts, a critical yet understudied domain.

Construction project success is strongly influenced by workforce competency, which can be demonstrated through certification. Despite regulatory requirements in Bali Province mandating certified competent labor for both large- and small-scale projects, limited research has examined the effect of workforce competency on project success when moderated by certification and grouped by project scale in Bali. This research aims to analyze the effect of construction workforce competency on construction project success and to examine this relationship when moderated by construction workforce certification. This study employs a quantitative approach with primary data collected through questionnaires distributed to 70 certified construction workers using purposive sampling, divided equally into large-scale and small-scale project groups. Data analysis was conducted using Structural Equation Modeling based on Partial Least Squares (SEM-PLS). The results indicate that, overall, construction workforce competency has a positive and significant effect on construction project success, with a t-statistic value of 3.834 and a p-value of 0.000. Based on the Multigroup Analysis (MGA), construction workforce competency continues to significantly influence construction project success in each group. There is no significant difference in the effect of workforce competency on construction project success between small-scale and large-scale construction projects, as indicated by a path coefficient difference of 0.166 and a p-value greater than 0.05 (0.283 > 0.05). Certification positively moderates the competency–success relationship (p = 0.013), with no significant difference in moderating effect between project scales (p = 0.452 > 0.05).

This study examines how Internet of Things (IoT) technologies are supporting global education. It notes that IoT is improving assessment methods, increasing student engagement, enabling personalized learning, and strengthening educational connections across countries. It also highlights issues related to privacy and cybersecurity. Using a mixed research methodology, data were collected from 210 students and 158 teachers through questionnaires. Interviews were also conducted with 58 teachers. Quantitative data were performed using Multivariate Analysis of Variance (MANOVA) and Partial Least Squares Structural Equation Modelling (PLS-SEM) methods; qualitative data were performed using NVivo. Results indicated that IoT-based assessments enhance fairness and accuracy in grading and increase student participation. However, data security and privacy challenges remain. Therefore, secure digital systems need to be developed, digital skills of teachers and students need to be improved, and IoT tools need to be used in a way that is compatible with teaching methods.

Introduction: Patient safety remains a critical global health agenda, as emphasized by the WHO and IOM. Fostering a robust patient safety culture within hospitals is paramount for minimizing adverse events and improving the quality of care. Understanding the psychosocial factors that drive this culture is essential for effective organizational interventions. This study aims to explore the direct and indirect effects of transformational leadership and team cooperation on patient safety culture, with a particular focus on assessing the mediating function of motivation within these relationships among healthcare professionals. Methods: An analytical cross-sectional research design was applied in this study. Study utilized a survey to collect data from 198 Healthcare Providers (HCPs) at Sulianti Saroso Infectious Disease (SSIDH). The primary instrument was the Hospital Survey on Patient Safety Culture (HSOPS) Version 2.0. Data analysis involved Structural Equation Modelling (SEM) based on Partial Least Squares (PLS-SEM) using SmartPLS 4.0 to test the proposed causal relationships. Results: Descriptive analysis showed that the variables of Transformational Leadership, Team Cooperation, Motivation, and Patient Safety Culture were all in the moderate category. However, hypothesis testing revealed significant findings. Both transformational leadership and team cooperation demonstrated a direct and significant positive influence on patient safety culture. Crucially, motivation was found to significantly mediate the relationship between transformational leadership and safety culture, as well as the relationship between team cooperation and safety culture. Conclusion: This study confirms that transformational leadership and teamwork are crucial factors that effectively enhance patient safety culture. The central finding of this study is the vital role of motivation as a psychological mechanism that translates managerial initiatives and team collaboration into proactive safety behaviors. Therefore, the practical recommendations from this research focus on strategies that directly target motivation, such as strengthening programs for recognition and responsibility, accompanied by improved interprofessional communication and more specific leadership training programs.

ABSTRACT This study examines the structural relationships among teaching innovation, creativity, social interaction, training intensity, Study Program, ICT competence, and pedagogical competence among in-service early childhood teachers in Indonesia. A quantitative explanatory design was employed, with data collected from 351 early childhood teachers who are alumni of PGPAUD, PIAUD, and PKAUD programs. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4. The findings reveal that social interaction is the strongest predictor of pedagogical competence, followed by creativity and teaching innovation. ICT Competence demonstrates a significant but modest direct association with pedagogical competence and functions as a weak mediator. Teaching innovation shows the strongest relationship with ICT, indicating that exposure to innovative instructional practices during teacher preparation is positively related to digital skills development. Conversely, training participation and Study Program are not significantly associated with ICT or pedagogical competence, suggesting inconsistencies in training quality across programs. The structural model explains 66.1% of the variance in pedagogical competence, indicating strong predictive power. This study contributes an integrated competence model incorporating social, creative, and technological dimensions of early childhood teacher preparation, with practical implications for curriculum design and training program development.

Analysis of the influential factors of depression in the elderly based on CHARLS through partial least squares structural equation and random forest modeling.

How perceived teacher support boosts learning engagement: The chain mediating roles of second language grit and foreign language enjoyment.

Mid-infrared spectroscopy combined with machine learning for rapid detection of caffeine in creatine supplements: Supporting food safety and product integrity.

Atractylodes macrocephala polysaccharide alleviates DSS-induced colitis through coordinated regulation of lipid metabolism, the bile acid-cAMP-JNK axis, and intestinal barrier function.

Voltammetric analysis of entacapone, levodopa, and carbidopa in tablets: A chemometric approach.

Continuous leachate irrigation as an ammonia source enhancing methane oxidation in landfill biocover soils.

This study examined the levels of and relationship between resilience, empathy, and professional competence among emergency nurses in Palestine. Emergency nurses working in conflict-affected regions such as Palestine encounter extreme stressors that may adversely impact their resilience, empathy, and professional competence. These factors are vital for sustaining high-quality nursing care, yet their interrelationships remain insufficiently understood. A cross-sectional design was employed, recruiting 236 emergency nurses from governmental hospitals across the West Bank, Palestine. Data were collected using the Connor-Davidson Resilience Scale, Toronto Empathy Questionnaire, and the short Nurse Professional Competence Scale. Data analysis involved IBM SPSS Statistics 26.0 and SmartPLS 4.0, applying structural equation modeling to assess relationships among variables. Participants had low resilience (M = 72.8, SD = 26.7), above-average empathy (M = 46.3, SD = 13.1), and high professional competence (M = 78.0, SD = 10.7). Empathy did not directly predict professional competence (β = 0.11, p = 0.13) but significantly predicted resilience (β = 0.96, p < 0.01). Resilience strongly predicted professional competence (β = 0.86, p < 0.01) and fully mediated the empathy-competence relationship (indirect effect = 0.81, p < 0.01). The mediation effect underscores resilience as a pivotal mechanism through which empathy influences professional competence in high-stress, conflict-affected settings. Enhancing resilience is essential to translate empathy into effective professional performance among emergency nurses in Palestine. Interventions focusing on resilience-building and emotional regulation can improve nurses' competence, reduce burnout, and support sustainable quality nursing care delivery. Policymakers should prioritize resilience enhancement strategies in nursing education and workplace policies, especially in conflict-affected healthcare environments.