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Volume 14, Issue 54 (9-2015)
Journal of Psychological Science 2015, 14(54): 193-207 |
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Pournaghash-Tehrani S, Talaei A, Farahani H. (2015). Determining the relationship between personality dimensions and motivation to job satisfaction using artificial neural networks . Journal of Psychological Science. 14(54), 193-207.
URL: http://psychologicalscience.ir/article-1-239-en.html
URL: http://psychologicalscience.ir/article-1-239-en.html
Tehran University , amirtalapash@gmail.com
Abstract: (2583 Views)
The present study aimed to explore the relationship between personality dimensions and motivation to intrinsic job satisfaction among Zob-Ahan Esfahan steel-making company employees. The artificial neural networks model was used for analyzing the data.
202 employees completed TCI-56, motivation at work scale (MAWS) and job satisfaction scale (JSS). Results revealed that identified motivation, intrinsic motivation and self-directedness were respectively the most important factors in predicting intrinsic job satisfaction.
202 employees completed TCI-56, motivation at work scale (MAWS) and job satisfaction scale (JSS). Results revealed that identified motivation, intrinsic motivation and self-directedness were respectively the most important factors in predicting intrinsic job satisfaction.
Keywords: job satisfaction, Cloninger personality theory, self-determination theory, artificial neural networks.
Type of Study: Research |
Subject:
General
Received: 2019/07/20 | Accepted: 2019/07/20 | Published: 2019/07/20
Received: 2019/07/20 | Accepted: 2019/07/20 | Published: 2019/07/20
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This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License. |
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)