Identifying the Effective Components on Talent Management of the Staff of the Central Organization of Islamic Azad University

Abstract

Purpose: The purpose of this study was to identify the strategic-indigenous components affecting the talent management of the staff of the Central Organization of Islamic Azad University.Methodology: The research method was mixed (qualitative-quantitative). The statistical population in this study was all experts in the field of talent management, which was done after 13 interviews. In addition, semi-structured interviews with university experts in 2009 were conducted in the form of descriptive, interpretive and selective codes, and the validity was determined in two ways: 1- The interview questions were fitted by 4 experts 2- The interview process by two colleagues To determine the reliability of Cohen's Coupon formula (0.533) was obtained which showed high reliability. . In order to conduct this research, in addition to the documentary study, the content analysis technique with MAXQDA12 software was used to identify the dimensions and components. SPSS25 software was used for Delphi methodFindings: According to the interviews, 385 initial codes were extracted in this process. With multiple revisions and integration of codes based on similarity and in several stages, finally 11 main components that define talent management along with 5 main themes (many of which were obtained in the research literature section) and finally 67 indicators and also 4 sub-dimensions as filtering dimensions (filters) and for them 8 components that define eachConclusion: The results showed that (dimension of talent absorption system, talent promotion system, talent retention system, development and education system and talent evaluation and discovery system) were identified as the main dimensions of talent management and also in 2 Delphi rounds of case components The evaluation was performed to determine the validity and reliability. In the first round, 23 indicators were removed and in the second round, 44 final indicators were approved with a Kendall coefficient of 0.654.