Designing a Digital Leadership Model for Human Resource Managers in Knowledge-Based and High-Tech Companies in Tehran Province Using a Mixed-Methods Approach

Abstract

This study aimed to design and validate a digital leadership model for human resource managers in knowledge-based and high-tech companies in Tehran Province. This applied study employed an exploratory sequential mixed-methods design. In the qualitative phase, systematic grounded theory was adopted, and data were collected through semi-structured interviews with 12 university academics and experts in management and human resource management, selected through theoretical purposive sampling until theoretical saturation was achieved. Qualitative data were analyzed through open, axial, and selective coding. In the quantitative phase, the statistical population consisted of 612 human resource managers working in knowledge-based and high-tech companies, from whom 236 participants were selected using stratified random sampling. Data were collected using a researcher-developed questionnaire derived from the qualitative findings. Content validity was assessed through expert judgment and the content validity ratio, while reliability was evaluated using Cronbach’s alpha. Confirmatory factor analysis and structural equation modeling were performed using LISREL. Confirmatory factor analysis demonstrated that the factor loadings of the observed indicators across the proposed dimensions were within acceptable ranges, while the corresponding t-values exceeded 1.96, indicating statistically significant relationships at the 0.05 level. The final model comprising causal conditions, contextual conditions, intervening conditions, strategies, and consequences was empirically confirmed. The overall structural model also demonstrated satisfactory goodness of fit (χ²=475.09, df=247, χ²/df=1.923, RMSEA=0.057, CFI=0.97, IFI=0.95, RFI=0.96, GFI=0.91, and AGFI=0.90), supporting the adequacy of the proposed measurement and structural framework. The proposed model demonstrated satisfactory structural validity and overall fit and can provide a comprehensive framework for identifying, developing, and evaluating digital leadership among human resource managers in knowledge-based and high-tech companies. The model may facilitate the alignment of human resource capabilities with digital transformation requirements and strengthen organizational readiness for digitally driven change.