The Architecture of Talent Identifying Process at National Elite Foundation: CM and SSM Hybrid Algorithm

Within the knowledge based economy, talents are known as a strategic talent in order to achieve sustainable competitive advantage as well as a criterion for growth in different organizational and social level. Thus, in recent studies, talent management architecture has emphasized on exploring and identifying talents in different fields. Accordingly, the present study aimed to provide a model of talent identifying process at the Iran National Elite Foundation (INEF). This study is conducted based on a descriptive-exploratory study with a developmental-applied approach. The statistical population of the research includes the scientific lasting faces of the country as well as top managers of the INEF. The statistical sample was selected through a purposeful judgment of 25 people. Data collection tools were library studies and semi-structured interviews with experts. Data were analyzed based on qualitative approach and based on a hybrid algorithm of the soft system methodology and cognitive mapping. The findings proposed a model to identify talents in INEF including two methods of elite selection as active and passive manner. The results showed that the active process of elite selection includes two nominating and searchable methods and the passive process of elite selection includrs two selective and self- assertive methods.