Document Type : Original Research Manuscripts

Authors

1 PhD Candidate in Public Administration, Islamic Azad University, Dehaghan Branch

2 Assistant Professor of Management, Islamic Azad University, Dehaghan Branch

3 Associate Professor, Department of Management, Islamic Azad University, Dahaghan Branch

Abstract

This research aimed to improve organizational efficiency in Iran's administrative system based on knowledge-based human resource management. The research was conducted using mixed methods. The grounded theory was used in the qualitative part, and in the quantitative part, the structural equation model with partial least squares approach was used. In the qualitative part, the statistical population, according to its subject area, included 10 elites and experts of the telecommunications company. Their opinions were collected using semi-structured interviews. The interviews were entered into the ATLAS TI software.  To fit the model, a questionnaire was designed using the identified codes. In the quantitative part of the current research, in addition to the elites of the telecommunications company, some members of top managers (15 people) from twenty units of the telecommunications company in the country were also added to the statistical population. According to the statistical population of 600 people, the studied sample included 234 people calculated based on Morgan's table. The information collected from the questionnaires was analyzed using SMARTPLS 3 software. Based on the analysis of the identified codes, a model with causal, strategy, consequence, intervention, and contextual components was determined. Also, in the structural equation model analysis, the model was confirmed. The results indicated that to increase organizational efficiency, managers should localize knowledge-based human resource management practices in organizations. In addition, it is important to impart appropriate knowledge, training, and expertise to employees so that they feel motivated and highly skilled in their jobs.

Keywords

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