Developing a Learning Organization Model for the Department of Environment Using a Mixed-Methods Approach: A Case Study of the Tehran Department of Environment

Abstract

This study aimed to develop and validate a learning organization model tailored to the characteristics, requirements, and organizational context of the Tehran Department of Environment. This developmental study employed a mixed-methods approach. In the qualitative phase, 15 experts from the Department of Environment with doctoral degrees and relevant professional experience were selected through purposive sampling until theoretical saturation was achieved. Data were collected through in-depth semi-structured interviews and analyzed using thematic analysis. The validity of the qualitative findings was assessed using Lawshe’s coefficient, while coding reliability was examined using Holsti’s method. In the quantitative phase, 228 employees and managers of the Tehran Department of Environment were randomly selected. A questionnaire developed from the qualitative findings was used for data collection. Face and construct validity and instrument reliability were assessed, and confirmatory factor analysis and model validation were conducted using partial least squares structural equation modeling (PLS-SEM) in SmartPLS. Inferential analysis showed a Kaiser–Meyer–Olkin value of 0.907, while Bartlett’s test of sphericity was significant at p<0.05, confirming sampling adequacy for factor analysis. The t-values for all indicators and items exceeded the critical value of 1.96, supporting the significance and validity of the measurement and structural relationships. The R² values of the model dimensions ranged from 0.617 to 0.828, with systems thinking demonstrating the highest explained variance. All Q² values were positive, with an overall mean of 0.454, indicating satisfactory predictive relevance. Cronbach’s alpha coefficients exceeded 0.70 for all constructs, composite reliability values were acceptable, and all average variance extracted values exceeded 0.40. Furthermore, the overall goodness-of-fit (GOF) index was 0.568, indicating satisfactory model fit. The proposed model demonstrated satisfactory validity, reliability, predictive relevance, and structural fit and may provide a practical framework for developing a learning organization within environmental agencies by strengthening continuous learning, knowledge management, systems thinking, adaptability, and organizational effectiveness.