Volume 16, Issue 36 (2-2025)
3 2025, 16(36): 1-13 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Ostovar M, Rahdarpour J. Identifying Factors Affecting Smart Decision-Making in Human Resource Management Based On Human Data Analysis with Artificial Intelligence. 3 2025; 16 (36) :1-13
URL: http://jnraims.ir/article-1-386-en.html
URL: http://jnraims.ir/article-1-386-en.html
Master’s in Public Management, Management Department, Islamic Azad University, Zabol Branch, Zabol, Iran
Abstract: (112 Views)
This research was conducted with the aim of identifying factors affecting smart decision-making in human resource management based on human data analysis with artificial intelligence. The present research is in the field of applied and development research in terms of its purpose. The statistical population of the present research consists of 10 experts and human resource managers of technology-based companies in Tehran. In this research, two library and field methods were used to collect information. A paired comparison questionnaire was used to collect field information, the validity and reliability of which were examined and proven. Also, in this research, a literature review was used to identify indicators. Also, the AHP technique was used to rank the research indicators. The results showed that the factors affecting smart decision-making in human resource management based on human data analysis with artificial intelligence include three individual, technical, and organizational components. The results also showed that among these factors, individual factors are in the first priority, technical factors are in the second priority, and organizational factors are in the third priority.
Keywords: Smart Decision-Making, Human Resource Management, Human Data Analysis, Artificial Intelligence
Type of Study: Research |
Subject:
General
Received: 2025/01/18 | Accepted: 2025/02/28 | Published: 2025/02/28
Received: 2025/01/18 | Accepted: 2025/02/28 | Published: 2025/02/28
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
