Journal of Management and Business Solutions 3092-7226 In Press 2027 05 01 Quantitative Elucidation of an Electronic Human Resource Management Model Based on Knowledge Management in the Social Security Organization Through Structural Equation Modeling Quantitative Elucidation of an Electronic Human Resource Management Model Based on Knowledge Management in the Social Security Organization Through Structural Equation Modeling 1 15 EN Journal Article 2026 02 11 <p>This study was conducted with the aim of quantitatively explaining an electronic human resource management model based on knowledge management. The research method was descriptive-correlational and classified as an applied study. In terms of data collection, the study employed a survey research method. The statistical population consisted of all employees of the Social Security Organization in Ardabil Province who possessed academic degrees (associate, bachelor’s, master’s, and doctoral degrees) and were employed in the organization, totaling 448 individuals. The sampling method was probability sampling using stratified random sampling. Cochran’s formula was used to determine the sample size, and based on this formula, a sample of 208 participants was selected. A researcher-made questionnaire (derived from the components extracted during the qualitative phase) was used to measure the variables. The validity of the instrument was confirmed through consultation with university faculty members and academic experts. Its reliability was also confirmed through Cronbach’s alpha coefficient, which was calculated to be higher than 0.70. The research variables were categorized into five comprehensive clusters: (1) technological development (human resource productivity, innovative attitude, electronic management, and job flourishing); (2) electronic knowledge (knowledge creation, knowledge application, knowledge enhancement, and knowledge transfer); (3) managerial requirements (electronic satisfaction, electronic training, improvement of labor relations, organizational objectives, and talent management); (4) organizational variables (environmental adaptability, information technology, professional development, technology culture, technology-based human resource development, and electronic skills); and (5) human resource variables (electronic performance appraisal, electronic compensation, and electronic recruitment). The results of confirmatory factor analysis indicated that the model demonstrated adequate and acceptable fit. Furthermore, the results of structural equation modeling revealed that the relationships among the variables were positive. The findings of the present study provide an appropriate guideline for the implementation of knowledge-based electronic human resource management in organizations.</p> https://www.journalmbs.com/index.php/jmbs/article/download/301/389