Identification and Validation of Intervening Factors in Human Resource Training Policymaking (Mixed Study)

Subject Areas : Human Capital Empowerment

abdollah mooharramzadeh ¹ , Behnam Talebi ² , zarrin daneshvar ³

1 - Ph.D. student in management, Islamic Azad University, Tabriz branch, Tabriz, Iran
2 - Corresponding Author, Department of Educational Sciences, Islamic Azad University, Tabriz Branch, Tabriz, Iran
3 - Corresponding Author, Department of Educational Sciences, Islamic Azad University, Tabriz Branch, Tabriz, Iran

Received: 2019-12-14 Accepted : 2020-06-29 Published : 2020-08-22

Keywords: Policymaking, Human Resource Training, Intervention Factors,

Abstract :

This research has been conducted with the aim of identifying and validating the intervening factors in human resource training policymaking in one of the country's banks. This research is a combination of qualitative grounded theory approach with semi-structured interview tools and quantitative survey approach using qualitative study questionnaire. The number of participants in this study in the qualitative stage of 14 experts with obvious cases sampling method was selected and in the quantitative stage, 300 employees and branch managers were one of the banks in the country by random cluster sampling method and were selected according to the northern, southern, central, western and eastern regions of the country. For data analysis in qualitative research, content analysis based on continuous comparison method of Strauss and Corbin, in qualifying qualitative findings, refer to experts and participants in the research and to validate the data in quantitative research, confirmatory factor analysis of the first and second order used . The results of open, axial and selective coding showed that the intervening factors can be classified into three themes: non-working considerations, executive problems and infrastructural problems, and 12 sub-themes. In the validation of qualitative findings, three sub-themes were eliminated and nine sub-themes were confirmed in the quantitative validation stage. The average adjusted coefficient of the model is 0.86 and the good of fitness the quantitative model is 0.52 and is very high.

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