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| dc.rights.license | CC BY | eng |
| dc.contributor.author | Zheng, Fei | cze |
| dc.contributor.author | Zhao, Chenguang | cze |
| dc.contributor.author | Usman, Muhammad | cze |
| dc.contributor.author | Poulová, Petra | cze |
| dc.date.accessioned | 2025-12-05T14:39:17Z | |
| dc.date.available | 2025-12-05T14:39:17Z | |
| dc.date.issued | 2024 | eng |
| dc.identifier.issn | 0018-9391 | eng |
| dc.identifier.uri | http://hdl.handle.net/20.500.12603/2175 | |
| dc.description.abstract | In the rapidly evolving landscape of human resources and talent acquisition, the impact of the usage of artificial intelligence (hereafter, AI) on recruitment biases has emerged as a pivotal and transformative subject of study. Therefore, this study aims to critically evaluate the impact of AI usage on recruitment biases, particularly in the context of China. The data were gathered through a survey of 423 respondents working in the manufacturing sector. We use a cross-sectional dataset and various diagnostics (i.e., reliability and collinearity tests). The empirical findings using multivariate regression techniques suggested that Al usage is reshaping the recruitment process by offering innovative solutions to tackle biases that have pervaded the hiring process for years. However, human involvement is indispensable in the recruitment process, alongside the use of AI. Although the use of AI can efficiently handle tasks such as resume screening and data analysis, human judgment brings essential qualities to the hiring process. Human recruiters possess the ability to assess a candidate's soft skills, cultural fit, and emotional intelligence, as these qualities are challenging for AI to comprehend. The policy implications of the study recommend that by combining the strengths of AI efficiency with human insight, organizations can create a recruitment process that is not only objective and efficient but also considerate, ethical, and aligned with the values and goals of the company. | eng |
| dc.format | p. 14155-14167 | eng |
| dc.language.iso | eng | eng |
| dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | eng |
| dc.relation.ispartof | IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, volume 71, issue: August | eng |
| dc.subject | Artificial intelligence | eng |
| dc.subject | Recruitment | eng |
| dc.subject | Companies | eng |
| dc.subject | Data analysis | eng |
| dc.subject | Task analysis | eng |
| dc.subject | Reliability | eng |
| dc.subject | Productivity | eng |
| dc.subject | Artificial intelligence (AI) | eng |
| dc.subject | human resource management | eng |
| dc.subject | recruitment biases | eng |
| dc.title | From Bias to Brilliance: The Impact of Artificial Intelligence Usage on Recruitment Biases in China | eng |
| dc.type | article | eng |
| dc.identifier.obd | 43881287 | eng |
| dc.identifier.wos | 001300990700006 | eng |
| dc.identifier.doi | 10.1109/TEM.2024.3442618 | eng |
| dc.publicationstatus | postprint | eng |
| dc.peerreviewed | yes | eng |
| dc.source.url | https://ieeexplore.ieee.org/document/10634779 | cze |
| dc.relation.publisherversion | https://ieeexplore.ieee.org/document/10634779 | eng |
| dc.rights.access | Open Access | eng |