talent

Purpose: The present study aims to investigate the relationship between smart talent management and meritocracy in order to provide the expressive characteristics of the selection, appointment and maintenance of managers. Methodology: The research method is descriptive survey and the required information has been collected using a researcher-made questionnaire that its validity has been determined from the available resources and through expert opinion and its reliability has been determined by calculating the Cronbach's alpha coefficient (.882). The statistical population of the present study includes the associate professor faculty members and higher rankings and staffs having MA and higher degrees, i.e. a total of 1,200 people. Sampling method is stratified random sampling through which 291 people are selected as the statistical sample. Findings: Findings of exploratory factor analysis show that strategy, attraction, evaluation and discovery of talents are the main components of talent management, and organizational learning, knowledge expansion and sharing are the main components of knowledge management. Among the 13 dimensions of talent management, the development of talent with a standard coefficient (.90) and preservation of talent with a standard coefficient (.88) are the most effective ones, respectively. Discussion: Among the 13 dimensions of knowledge management, expansion and sharing with a standard coefficient (.95) and organizational learning with a standard coefficient (.88) are the most effective ones, respectively. Also, confirmatory factor analysis confirms the relationship between smart talent and meritocracy with a standard coefficient (1.06), and test statistics has evaluated the severity (correlation coefficient) of this relationship (.299).

Talent is a fundamental quality in humans that entails personal and social differences. However, despite its importance, relatively few empirical studies have addressed identification and assessment of talents. An adequate exploration of any topic will require extensive knowledge about it. The Holy Quran, as the very words of the Creator, who created humans with a certain structure of existence, presents the most comprehensive knowledge. Therefore, this study drew on the Quran to present indicators for talent assessment using a qualitative approach. First, among all verses of the Quran, those with words somehow related to talent were selected, leading to a semantic web, which was then used to create a list of the most relevant words. Next, lexical and conceptual analyses and Quranic usage analyses of these words, along with content analyses of the verses containing them using tadabbur (Quranic Contemplation) methods, marked three words ( ni’mah – pleasant asset, sabīl – course, and faẓl – added privilege) as the main indicators for talent assessment. The findings showed that each of these indicators could be assessed in three areas, or axes, which included level of knowledge, level of yearning and level of access. Finally, the study suggests that, thanks to the comprehensive nature of the knowledge provided in the Quran, exploring the characteristics, components and dynamics of the three main words results in a far more wholistic framework for assessing human talents, which allows for more reliable and applicable results - compared to those provided by individualistic frameworks.