Hasan Asali; Sayyed Mohammad Reza Davoodi; Sayyed Hamid Reza Mirtavousi
Abstract
This research aims to present a knowledge development model for future managers based on talent management with a grounded theory approach in the Iranian Social Security Organization (headquarters). This research is applied in terms of purpose and exploratory in terms of method. It uses a mixed methods ...
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This research aims to present a knowledge development model for future managers based on talent management with a grounded theory approach in the Iranian Social Security Organization (headquarters). This research is applied in terms of purpose and exploratory in terms of method. It uses a mixed methods approach for data collection and analysis, qualitative and quantitative data analysis techniques- grounded theory and structural equation. The research tool in the qualitative part was a semi-structured interview. In the qualitative part, using the grounded theory method, data obtained from the interviews with 12 elites and qualified specialists of the Social Security Organization, which were analyzed manually and by using Atlas TI 8 software during three stages of open, central, and selective coding that resulted in generation of 19 categories. The results were presented in the form of a paradigm model that includes causal conditions (individual factors, organizational factors, lack of proper selection and knowledge and skills of employees), central phenomenon (future managers based on talent management and personality types), underlying conditions (organizational platform, selection of talents, use of talent) Intervening conditions (psychological factors, individual factors, managerial factors) and strategies (talent sourcing, empowering managers and employees, job and employee fit, succession planning, foresight, and cognitive strategy) and outcomes (organizational results, public satisfaction, futurization). In the quantitative part, the data obtained from the structural equation analysis questionnaire were analyzed using AMOS statistical software. Based on the outputs, the factor loadings of all the items of the standard model were higher than 0.3, and all the significant coefficients of the model were higher than 1.96.
Taimour JafarianDehkordi; Mohammadreza Dalvi Esfahan; Saeed Aghasi
Abstract
The purpose of this research was to present an organizational vitality model based on information management and human resource data. Human resource information management is a process that seeks to increase organizational capability through the organization's employees, which is considered one of the ...
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The purpose of this research was to present an organizational vitality model based on information management and human resource data. Human resource information management is a process that seeks to increase organizational capability through the organization's employees, which is considered one of the most important success factors. The research was designed in a mixed qualitative and quantitative method and benefited from the foundation's data strategy. In the qualitative part, the data obtained from in-depth interviews with 25 general managers of social security of the provinces of the selected country were based on purposeful sampling. In the quantitative part, 376 people from the lower-level employees of this organization were selected in different regions of the country by stratified random method and answered the questions of the researcher-made questionnaire. Qualitative data were analyzed using the Grounded Theory and the quantitative data were analyzed through confirmatory factor analysis using SPSS and AMOS software. The results obtained from the qualitative phase of the research led to the design of a proposed conceptual model of organizational vitality in the social security organization, and in the quantitative phase, using path analysis, validity of the conceptual model was. evaluated. From the practical point of view, the proposed model can be implemented by social security organization managers to create vitality among employees in order to reduce depression and boost productivity.
