Document Type: Original Article

Authors

1 Associate Professor at AllamehTabataba'i University

2 Associate Professor at AllamehTabataba& University, tehran, Iran

3 Assistant Professor atAllamehTabataba& University, Tehran, Iran

4 Ph.D. student, AllamehTabataba'i University, Tehran, Iran

Abstract

The study aims at providing a model for talent management in active knowledge-based companies in agricultural domain of Guilan Province. This applied and descriptive study with a mixed research method. In the qualitative part, an in-depth semi-structured interview with 30 experts was used and also the theoretical foundations and research background study were applied for qualitative data collection. For collecting data in the quantitative part, the survey study was used. The survey research data were collected through a researcher-made questionnaire. The target population consisted of 150 intermediate managers, supervisors, and deputies of knowledge-based organizations in Rasht, of which 108 participants were selected via purposeful sampling as the sample size of this study. The sampling size was determined via the table of Krejcie and Morgan. SPSS19 software and Smart PLS3 software were used to analysis the data. The results showed that the dimensions identified in the field of talent management in the knowledge-based companies were include: internal talent identification, external talent identification, socialization (making socialized), development and talents retention. Two components identified for internal talent identification include identification of talented employees and the selection of talented employees. Three factors consist of transformational leadership, organizational culture and employer brand have been identified as the underlying and effective factors on talent management in the knowledge-based companies of agriculture section in Rasht city. The transformational leadership style has the greatest impact on the talent management and the employer brand is in next ranking in terms of the effectiveness level on the talent management.

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