[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
:: Volume 3, Number 4 (12-2016) ::
3 2016, 3(4): 78-96 Back to browse issues page
Prediction of job satisfaction based on personality type and perceived social support
Somayyeh Fereidounpour *, Jafar Pouyamanesh, Hakami Mohammad
MS in General Psychology Islamic Azad University- Karaj Branch
Abstract:   (132 Views)

Introduction: since development of an organization considerably requires accurate hiring of human resources, their job satisfaction has been paid into attention in psychological studies.

Purpose: The present study was conducted to predict job satisfaction based on personality type and perceived social support.

Method: The statistical universe included all employees of Iran Khodro Car Making Company except the management categories (top managers, senior managers, directors, supervisors and night shoft workers). A sample size of 120 individuals was selected using cluster sampling method. The research tools included Smith’s Job Satisfaction Questionnaire, NEO Five-Factor Inventory and Bruwer’s Scale of Perceived Social Support. Pearson’s correlation coefficient and regression analysis were used for data analysis.

Results: The results indicated that neuroticism has a positive correlation with job promotion and extraversion has a positive correlation with family support, friends support, total score of social support, nature of work component, supervision and total score of job satisfaction. Agreeableness has a positive correlation with friends’ support, nature of work component, supervision and colleagues while it has a negative correlation with the component salary and benefits. Flexibility has a positive correlation with family support, total score of social support, nature of work and colleagues. Accountability has a positive correlation with family support, total score of social support, nature of work component and job satisfaction while family support had a significant correlation with none of the components of job satisfaction. The friends’ support has a positive correlation with nature of work, supervision, colleagues and total score of job satisfaction while it has a negative correlation with the component salary and benefits. The others’ support has a positive correlation with the components supervision, nature of work, salary and benefits and total score of job satisfaction while it has a negative correlation with the components job promotion and colleagues.

Conclusion: based on regression analysis results, the components friends’ support and social support could explain job satisfaction among predictor variable (five personality factors and social support). The components extraversion and neuroticism could explain the salary and benefits. The components agreeableness and friends’ support could explain the salary and benefits. The components friends’ support, others’ support and agreeableness explained the component supervision. The variables friends’ support, social support and flexibility explained the colleagues. The variables neuroticism, flexibility and extraversion explain the component job promotion.

Keywords: extraversion, personality type, perceived social support, job satisfaction and neuroticism.
Full-Text [PDF 889 kb]   |   Full text (HTML)   (197 Downloads)    
Type of Study: Applicable | Subject: Special
Received: 2016/12/1 | Accepted: 2017/01/17 | Published: 2017/01/17
Send email to the article author

Add your comments about this article
Your username or email:

Write the security code in the box >



XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Fereidounpour S, Pouyamanesh J, Mohammad H. Prediction of job satisfaction based on personality type and perceived social support. 3. 2016; 3 (4) :78-96
URL: http://shenakht.muk.ac.ir/article-1-278-en.html
Volume 3, Number 4 (12-2016) Back to browse issues page
فصلنامه علمی پژوهشی شناخت Shenakht journal of psychology & psychiatry
Persian site map - English site map - Created in 0.43 seconds with 789 queries by yektaweb 3461