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This research includes a study of the most important determinants that affect a very important phenomenon, which is—job leakage—as this phenomenon is considered one of the greatest obstacles that stand in the way of the stability of establishments and the control of the strategic goals and plans that management sets based on the competencies and human capital that A = πr2 the establishment possesses. The researcher used the Binary Logistic Regression technique to build a mathematical model to predict the likelihood of impact on the phenomenon of employee dropout by identifying (7) independent variables, which are: Gender—adequacy of salary—relationship with management—justice in the distribution of wages—work routine—workload—higher education, there is only one dependent variable, which is job dropout. The study was applied to a cluster sample selected from a group of employees working at the University of Technology. The number of sample members was estimated at (110) people who were targeted in a diverse way from the research community to increase the degree of comprehensiveness and credibility of the research and to cover a good range of opinions of workers in local institutions. The researcher reached a set of results, the most important of which are: The routine of work, then the adequacy of the salary, fairness in distribution, then the workload, then gender have a moral effect, according to the order, on the phenomenon of job dropout. There is no statistically significant impact of higher education and the relationship with the administration on the moral impact on the program.

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Building a Predictive Model About the Factors Influencing the Phenomenon of Job Dropout Using Binary Logistic Regression: An Analytical Study of a Sample of Institutional Workers

  • 章节

  • 发表日期：

    2025年

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  • Rajaa Kamil Majeed,
  • Ali Hussein Abd Ali,
  • Rawnak Kadhum,
  • Mayada Jaafer Naji Awni

摘要

This research includes a study of the most important determinants that affect a very important phenomenon, which is—job leakage—as this phenomenon is considered one of the greatest obstacles that stand in the way of the stability of establishments and the control of the strategic goals and plans that management sets based on the competencies and human capital that A = πr2 the establishment possesses. The researcher used the Binary Logistic Regression technique to build a mathematical model to predict the likelihood of impact on the phenomenon of employee dropout by identifying (7) independent variables, which are: Gender—adequacy of salary—relationship with management—justice in the distribution of wages—work routine—workload—higher education, there is only one dependent variable, which is job dropout. The study was applied to a cluster sample selected from a group of employees working at the University of Technology. The number of sample members was estimated at (110) people who were targeted in a diverse way from the research community to increase the degree of comprehensiveness and credibility of the research and to cover a good range of opinions of workers in local institutions. The researcher reached a set of results, the most important of which are: The routine of work, then the adequacy of the salary, fairness in distribution, then the workload, then gender have a moral effect, according to the order, on the phenomenon of job dropout. There is no statistically significant impact of higher education and the relationship with the administration on the moral impact on the program.