Presenting an Interpretative Structural Model for Promoting Intellectual Capital in the Database of Public Organizations

Improving intellectual capital in databases involves enhancing the productivity of information and knowledge stored in these systems to boost organizational and competitive value. The intellectual capital development model encompasses processes such as collecting, organizing, analyzing, and utilizing data to create new and value-added knowledge. This article aims to present an interpretive structural model for enhancing intellectual capital within the databases of public organizations. The research was conducted using a mixed-method approach, including the metasynthesis method and interpretive structural modeling. To achieve this objective, the fundamental categories for promoting intellectual capital were identified and validated. By establishing the causal relationships among these elements, the final model was developed. It is an applied-developmental research in terms of purpose and a survey-cross-sectional research in terms of data collection method. The statistical population for this study comprised experienced human resource managers at Tehran Municipality. The snowball sampling method was utilized, and the sampling process continued until theoretical saturation was achieved, with ۱۳ managers from Tehran Municipality ultimately participating in the study. The metasynthesis method was used to identify the underlying categories of intellectual capital. Additionally, a structural-interpretive model for intellectual capital promotion was presented. Data analysis was conducted using MaxQda and MicMac software. The results indicated that "organizational leadership, "organizational culture, and "organizational structure" influence the "expertise and skills of human resources, "media interactions" and "social customization. factors also affect "cooperation and participation, of "management of the relationship with the master of reference of "social excellence.

Keywords:

intellectual capital , Knowledge storage , Database , Government Organizations , Public Organizations