Job Satisfaction Prediction based on Job Motivation and Emotional Intelligence of Managers and Employees

Authors

  • Alipour Katigarie, Shiva Ph.D. Student of educational psychology, Khomein branch, Islamic Azad University, Khomein, Iran.
  • Davoudi, Hossein Assistant professor of counseling, Khomein branch, Islamic Azad University, Khomein, Iran.
  • Givaki, Ebrahim Lecturer of Management Department, Khomein Branch, Islamic Azad University, Khomein, Iran
  • Manzari, Ali Reza Assistant Professor of Educational Science Department, Kerman Branch, Islamic Azad University, Kerman, Iran.
Abstract:

Abstract Purpose: The aim of this study was to predict the job satisfaction in managers and staff of the university units in District 5. Methodology: Among the statistical population of the study, 130 people (55 females and 75 males) were selected by cluster sampling method. Data were collected using job satisfaction, emotional intelligence of Schutt, and job motivation questionnaires. Finding: For data analysis, Pearson correlation coefficient and multi-variable regression analysis were used simultaneously. So, the two predictor variables are a significant predictor of the criterion variable, that is, the variable of job satisfaction. The share of job motivation variable is higher than emotional intelligence. In other words, job motivation 57% and emotional intelligence 31% explain the variable of job satisfaction variance. Discussion: The results showed that there is a significant correlation between job satisfaction, job motivation and emotional intelligence, and on the other hand, emotional intelligence and job motivation are a significant predictor of job satisfaction.

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Journal title

volume 1  issue None

pages  112- 118

publication date 2018-01

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