Kajal Chheda

Artificial Intelligence (AI)-powered Human Resource Management (HRM) systems address inefficiencies in recruitment and employee retention. Traditional methods are slow, biased, and reactive. Integrating AI enables predictive insights, automated screening, and employee satisfaction monitoring, transforming HR practices into data-driven, strategic decision-making processes. This research aims to evaluate the impact of AI on improving recruitment efficiency and talent retention. It investigates whether AI-based tools significantly reduce hiring time, enhance job candidate fit, and predict attrition risk. Data was sourced from 1,000 anonymzed employee records, including 400 resumes, 280 satisfaction responses, and 320 attrition cases across the IT and finance sectors. Collected over a three-year period, the dataset supports recruitment analysis and employee retention prediction using AI-based models. Five variables were analyzed: recruitment time (RT), candidate-job match score (CJMS), employee satisfaction score (ESS), retention rate (RR), and AI-predicted attrition risk (APAR). These variables represent both continuous and ordinal data types, suitable for independent sample t-tests and regression analysis in SPSS 25. SPSS analysis showed significant reductions in recruitment time (p < 0.01) and improvements in job match scores. Among independent sample t-test results, the highest t-value was observed for CJMS (t = 22.15, p < 0.001). Spearman’s correlation indicated a strong positive link between satisfaction and retention. Regression analysis confirmed high predictive accuracy of AI-based attrition risk models. In regression findings, APAR had the highest R² value (R² = 0.42, p < 0.001). AI-powered HR systems significantly enhance recruitment efficiency and retention strategies. Statistical evidence confirms the effectiveness of AI in predicting attrition and improving candidate-job alignment, enabling organizations to make proactive, data-informed HR decisions and foster a more stable workforce.

Introduction: Effective communication mechanisms are vital for organizational success, influencing employee engagement and overall performance. Despite their importance, many organizations face challenges due to unclear or infrequent communication, which undermines trust and productivity. This research investigates the influence of communication mechanisms—including frequency, medium, formality, and clarity—on employee engagement and organizational effectiveness, with employee trust as a mediating factor.Methodology: Data were collected through a structured survey administered to 171 employees across various sectors. The survey measured communication practices, employee trust, and engagement using a 5-point Likert scale. Statistical analyses, including regression analysis, were conducted using IBM SPSS version 25 to examine the relationships among variables.Results: The analysis revealed that communication frequency and clarity significantly enhance Economic success (ES), and Operational efficiency (OE). Regression results indicated a strong positive correlation between clear communication and employee engagement (p < 0.01). Two-way communication (TWC), Transparency of communication (TC), Communication consistency (CC)and Employee engagement (EE) also contributed to improved trust and engagement.Conclusion: Findings highlight that communication clarity and frequency are critical drivers of employee engagement, facilitated by trust in communication. Organizations should prioritize enhancing communication quality and consistency to build trust, thereby fostering higher engagement and improved organizational effectiveness.

The study examines the benefits of imaginative teaching practices in enhancing educational quality by focusing on innovative pedagogical approaches. It aims to evaluate the influence of these performances on key variables, including Student Engagement (SE), Academic Performance (AP), Educational Satisfaction (ES), Creativity Development (CD), and Critical Thinking Skills (CTS). Using SPSS software, various statistical methods, such as x2 tests, ANOVA (Analysis of Variance), T-tests, and descriptive statistics, were employed to analyze data collected from educators. The findings reveal significant improvements across all measured variables, indicating that imaginative teaching practices effectively enhance student engagement, academic performance, critical thinking skills, creativity, and overall satisfaction with the educational experience. These results suggest that incorporating creative methods in teaching can create a more dynamic, engaging, and effective learning environment, ultimately leading to improved educational outcomes.

Employee behavior, decision-making, and cooperation across the supply chain network are all greatly influenced by organizational culture (OC). In supply chain outcomes (SCO), an understanding of the effect promotes efficiency overall, improves coordination, and maximizes performance. The structural equation modeling (SEM) technique was initially applied to experimentally analyze data from a survey of 85 enterprises using a quantitative approach. The relationships between cultures such as OC, market culture (MC), clan culture (CC), Hierarchy culture (HC), Professional culture (PC), Adhocracy culture (AC), and supply chain outcomes are analyzed in this research. The findings are evaluated using the combination of a reliability and validity test, multiple regression analysis. The SEM approach is employed to investigate the intricate correlation that exists between these cultural aspects and SCO. A more detailed comprehension of these linkages is provided by the simulation technique, which enables a thorough investigation of the ways in which each cultural feature affects SCO. Positive correlations between the independent variables (OC, AC, MC, HC, PC, and CC) and the dependent variable (SCO) are predicted. The majority of these relationships exhibit statistically significant positive impacts(p < 0.05), signifying noteworthy and substantial benefits for SCO. Furthermore, although OC, AC, MC, PC, and CC have substantial positive impacts, HC has a relevant but invisible effect. OC has a major influence on SCO, according to the study, with some cultural characteristics having a considerable impact on performance measures. Improved efficacy and efficiency in supply chain operations are fostered by a well-aligned culture.

The implementation of internet-based educational designs to enhance teaching and learning could be advantageous for higher education. There is not much research on digital methods of learning in physiotherapy education. The investigation examines and assesses methods of online learning in an effort to raise the standard of physiotherapy education. An extensive meta-analysis and evaluation of both randomized and non-randomized tests are the proposed methods of the research. A map was made of the digital initiatives and research mentioned in the list. Learning impacts for similar interventions were determined by means of meta-analysis. Five cohort investigations and ten randomized controlled trials make up the total of 15 researches included in the evaluation. Blended learning, remote learning, and the flipped classroom methodology were all used in 14 studies. In all, seven of the fifteen pieces of content were referenced in the flipped classrooms have statistically significant effects on learning, according to a meta-analysis for interaction uses on useful skills. Based on the findings, integrating pedagogical approaches is equally, if not more, more efficient than a regular classroom instruction in obtaining learning objectives. Results in online education did not show any discernible variations from traditional classroom training. It has been found that space learning and integrated learning are just as effective as traditional teaching approaches, if not more so, in the field of physiotherapy education. The meta-analysis found that using student-made videos, flipped classrooms, and interactive websites improved students' learning. Larger controlled trials are needed to validate these results. Research ought to investigate the ways in which online learning models can make possible students' assimilation in pragmatic abilities and behaviors, facilitate their understanding of concepts, enhance their memory of contents, and cultivate methods of learning. Further, it needs to examine digital learning materials and information bases.