UUM Electronic Theses and Dissertation
UUM ETD | Universiti Utara Malaysian Electronic Theses and Dissertation
FAQs | Feedback | Search Tips | Sitemap

The modifying effect of artificial intelligence on the relationship between human resource practices and organizational performance: an applied study in the field of manufacturing in Dubai

Almansoori, Abdelrahman Hassan Mohamed Abdulla (2022) The modifying effect of artificial intelligence on the relationship between human resource practices and organizational performance: an applied study in the field of manufacturing in Dubai. Doctoral thesis, Universiti Utara Malaysia.

[thumbnail of depositpermission_s903743.pdf] Text
depositpermission_s903743.pdf
Restricted to Repository staff only

Download (430kB) | Request a copy
[thumbnail of s903743_01.pdf] Text
s903743_01.pdf

Download (18MB)

Abstract

The success of any organization lies in the ability of human resources management staff to hire and select the best employees to perform the required duties and tasks, the ability to retain competent employees. Accordingly, the problem of the study is represented in the obstacles facing the human resources department in the field of manufacturing in Dubai to recruit the best employees so that they can accomplish the required tasks effectively and efficiently. The study aimed to know the effect of human resource practices (employee selection, employee recruitment, staffing process) on the performance of the organization, investigate the mediating effect of competitive advantage on the relationship between those human resource practices and the performance of the organization, in addition to investigate the moral effect of the use of artificial intelligence in analyzing the CV of employees and its potential contribution in the organization performance. The study used the quantitative method with a cross-sectional design, by using the questionnaire as a tool for data collection. The study population is equivalent to the total number of human resources workers in manufacturing industries in Dubai. The actual study sample consisted of (247) employees who were chosen randomly and the most important results indicate the success of the model as it can predict 78.2% of the organization's performance. The study found a positive statistically significant relationship between (employee selection, employee recruitment, staffing process) and organizational performance, there is a positive statistically significant relationship between (employee selection, employee recruitment, staffing process) and competitive advantage, the study also found that artificial intelligence has a positive moderate effect on the relationship between (employee selection, employee recruitment, staffing process) and competitive advantage. The whole combination of six research subjects show positive perceptions among the respondents. Likewise, there is a direct relationship between the three probabilities in the implementation of human resource management. Besides, the priority of the relationship based on the path coefficient value for employee recruitment is (ER) 0.201, for employee selection is (ES) 0.132 and for employee recruitment process is (SP) 0.372. The three variables show that there is 36.2% variance of organizational performance (OP). Meanwhile, the priority of the relationship based on the path coefficient value which is employee recruitment is 0.183, employee selection is 0.176 and the staffing process is 0.024. Meanwhile, the competitive advantage has a significant effect on organizational performance which is 0.281 and also has a good link in the relationship between the three variables and organizational performance.

Item Type: Thesis (Doctoral)
Supervisor : Othman, Muhammad Fuad and Siam, Mohammed R. A.
Item ID: 10624
Uncontrolled Keywords: Human Resource Management, Artificial Intelligence, Organizational Performance, Competitive Advantage, Manufacturing Industries
Subjects: H Social Sciences > HD Industries. Land use. Labor. > HD28-70 Management. Industrial Management
Divisions: Ghazali Shafie Graduate School of Government
Date Deposited: 31 Jul 2023 00:35
Last Modified: 31 Jul 2023 00:35
Department: Ghazali Shafie Graduate School of Government
Name: Othman, Muhammad Fuad and Siam, Mohammed R. A.
URI: https://etd.uum.edu.my/id/eprint/10624

Actions (login required)

View Item
View Item