International Journal of Nonlinear Analysis and Applications

Presenting a model for measuring the capabilities of human resource strategy in government organizations

Document Type : Research Paper

Authors

Department of Public Administration, Bonab Branch, Islamic Azad University, Bonab, Iran

Abstract

Since human resources are the most valuable factor for manufacturing, and the most important capital of every organization today, human resource planning (HRP) is one of the most underlying organizational plans. Planning to achieve skill and educational needs, and improvement of human resources can be the underlying factor for human resource planning. Over the years, human resources have been changed into the focus point of leading organizations and managers. It can be regarded as the most underlying organizational capital, for which no alternative can be considered. This study is aimed at presenting a model to measure the capabilities of human resources strategies. At first, wide library investigations were done in this field and existing models. Then, a basic model was selected to measure the capabilities of human resources within the governmental organizations to switch the study. Interviews were done with academic, and government experts and other scholars to test the validity and reliability of the model. the qualitative model validation was done using interviews, and the sampling method was snowball sampling. The model revision was done using qualitative methods. For model designation, the interpretive-structural modelling (ISM) technique, and fuzzy approach were used. The research instrument in this study was a questionnaire. According to obtained results, the experts counted essential factors affecting the capabilities of human resource strategy as follows: value, scarcity, being inimitable, without substitution, taking required behaviours, having required competencies, sufficient motivation of personnel, and productivity.

Keywords

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International Journal of Nonlinear Analysis and Applications
Volume 13, Issue 2
July 2022
Pages 939-951
  • Receive Date: 06 October 2021
  • Revise Date: 13 November 2021
  • Accept Date: 10 December 2021