Since the onset of the COVID-19 pandemic, academic research has primarily focused on the challenges posed by flexible working arrangements. However, there has been a lack of exploration into managers’ intentions to either promote or reject remote work. This paper utilizes a TAM analysis to examine managers’ attitudes and motivations towards implementing telework in a sample of European companies. Our findings reveal that this intention is largely influenced by their perception of its usefulness. Additionally, telework is more likely to be accepted when managerial teams believe that those who hold significance to them also support the implementation of flexible work practices in their companies. Our research contributes to the existing literature by considering the impact of job performance, quality of output, and digital skills on telework adoption. The results confirm that skills related to communication and team building are crucial competencies for successfully implementing telework. The ability of leaders to effectively build, motivate, recognize, and hold accountable teams in virtual environments can make all the difference.

The purpose of this study was to investigate the published literature on human resource management and school performance from January 2012 to December 2022. Numerous literature evaluations have been conducted on human resource management and organizational performance, but school or teacher performance has received less attention than organizational performance. The PICOC (population, intervention, comparison, outcome, and context) technique is integrated into each stage of the PSALSAR framework to assure the study’s objective and comparability. This in-depth research is conducted in three stages: identifying pertinent keywords, screening pertinent papers, and selecting pertinent publications for review utilizing the PRISMA (Preferred Reporting Items for Systematic Reviews and Mata Analysis) technique. This made a final database with 44 publications that met the study’s requirements for inclusion. This study reveals that HRM practices and school performance are correlated. The results of the research identify the eight most essential HRM practices for improving school performance, which included planning, organizing, recruitment and selection, training and development, performance management, employee relations and involvement, reward and compensation, health, safety, and work-life balance. Leadership style, motivation, satisfaction, productivity and task performance, competency, culture and climate, empowerment, and commitment were among the performance-influencing elements.

The main objective of the study was to examine factors that influence employee performance in general and, more specifically, in public enterprises. The research approach was qualitative, with an in-depth literature review and content analysis. The findings of the study reflect that some factors have a positive and some have a negative influence on employee performance. The study also shows a significant relationship between factors and employee performance, which in turn has a multiplier effect on employee development. Recommendations include the need to provide resources for employee training and development, and the strategic aims and objectives of public enterprises should be aligned with the training and development programs.

Proactive coping behavior has been considered an important personal job resource for employees. Organizations have paid considerable attention to the proactive coping behavior of employees to maintain their competitive advantage. The purpose of the current study is to discover the relationship between organizational job resources, work engagement, and proactive coping using structural equation modeling. The participants were 340 licensed Chinese social workers. In the rapidly growing social work sector in China, social work organizations require psychologically connected and dedicated social workers. Findings include the effect of organizational job resources and work engagement on proactive coping. Based on the results, impacts on organizational management are discussed.

The high demand for quality healthcare services in Portugal is generating concerns about meeting the optimum number of healthcare professionals in the private sector, such as doctors and clinicians. Critical interventions are currently in progress, aiming to provide quality healthcare that will be accessible and sustainable through actionable retention strategies such as investing and developing human capital, introducing better conditions of service to attract and retain talent in the private healthcare sector, and prioritizing the needs of patients. The objective of this study is to understand which factors promote the migration of physicians from the public to the private sector according to the theoretical assumptions of incentives. In this context, a phenomenological study was carried out, using semi-structured interviews with fifteen physicians working in the private health network. Content analysis was done using NVivo 12. The results indicate that performance evaluation in the private sector exists but has no alignment with incentives. The condition makes the private healthcare sector unattractive, however, other policies of remuneration remain promising. Current proposals that could revive the image of the sector include collective decision-making and strong labour relations advocacy for physicians in the private sector.

Machine analysis of detection of the face is an active research topic in Human-Computer Interaction today. Most of the existing studies show that discovering the portion and scale of the face region is difficult due to significant illumination variation, noise and appearance variation in unconstrained scenarios. To overcome these problems, we present a method based on Extended Semi-Local Binary Patterns. For each frame, an aggregation of the pixel values over a neighborhood is considered and a local binary pattern is obtained. From these a binary code is obtained for each pixel and then histogram features is computed. Adaboost algorithm is used to learn and classify these discriminative features with the help of exemplar face and non-face signature of the images for detecting the location of face region in the frame. This Extended Semi Local Binary Pattern is sturdy to variations in illumination and noisy images. The developed methods are deployed on the real time YouTube video face databases and found to exhibit significant performance improvement owing to the novel features when compared to the existing techniques.