International Journal of Nonlinear Analysis and Applications

Structural equation modeling of the relationship between job descriptions and employee competencies in drug distribution companies

Document Type : Research Paper

Authors

Department of Management, Kerman Branch, Islamic Azad University, Kerman, Iran

Abstract

The aim of this study was to model the structural equations of the relationship between job descriptions and employee competencies. The existing research is descriptive research in terms of practical and developmental purpose and correlational descriptive research in terms of method. The statistical population of the study includes all the work of employees of pharmaceutical companies in Tehran from 1399 to 1870 people, of which 800 people were selected as a sample by simple random sampling method. Four researcher-made questionnaires were used to collect data, which included an 80-item questionnaire describing job descriptions with a validity of 0.84 and reliability of 0.967, a 98-item questionnaire on employee competencies with a validity of 0.86 and reliability of 0.953. Structural equation modeling was used to analyze the data using SPSS and AMOS22 software. The results showed that the proposed model has an acceptable fit to explain the relationship between job descriptions and employee competencies. So that there is a positive and significant relationship between job descriptions of physical abilities (including physical health, and physical ability); intellectual abilities (including intelligence, memory, creativity, innovation, and flexibility); social skills (including social interactions, verbal skills, nonverbal skills, emotion management, social responsibility, emotional intelligence) and mental ability (including mental health, adjustment and vitality) and competencies of pharmaceutical companies employees.

Keywords

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International Journal of Nonlinear Analysis and Applications
Volume 14, Issue 7
July 2023
Pages 179-188
  • Receive Date: 04 August 2022
  • Revise Date: 21 September 2022
  • Accept Date: 01 October 2022