Investigating the Effect of Human Resource Management Automation and Organizational Intelligence Capabilities on Job Satisfaction

Abstract

The present study aims to investigate the effect of intelligent human resource management and organizational smart capabilities on job satisfaction among employees of the Central Administration of Islamic Azad University. This research is applied in terms of purpose and descriptive in terms of data collection method. The statistical population consists of 2,085 employees from the University’s Central Administration, from which a sample of 325 individuals was selected using a multi-stage cluster random sampling method based on the Morgan Table.
Standardized instruments were employed to measure the research variables: Intelligent Human Resource Management was assessed using the questionnaire developed by Abbasi and Esmaeili (2024), consisting of 65 items among nine subscales. Organizational Smart Capabilities were measured with the Makilav (2021) questionnaire, comprising 46 items among eight subscales; and Job Satisfaction was assessed using the Minnesota Satisfaction Questionnaire, including 19 items among six subscales. All questionnaires were scored using a Five-Point Likert Scale.
Data analysis was conducted using SPSS version 27 for descriptive statistics and Smart PLS version 4 for structural equation modeling. The results of hypothesis testing indicated that Organizational Smart Capabilities have a positive and significant effect on Job Satisfaction (Path Coefficient = 0.467, t-value = 5.999, p-value = 0.000). Similarly, Intelligent Human Resource Management also showed a positive and significant effect on Job Satisfaction (Path Coefficient = 0.412, t-value = 5.379, p-value = 0.000). These findings suggest that strengthening technological infrastructures and the strategic utilization of human resources can play a significant role in enhancing employee job satisfaction.