The acceptance of artificial intelligence in Performance Evaluation and Training Development: Analysis of Influencing from the Perspective of Employees

Hong, Juan (2025) The acceptance of artificial intelligence in Performance Evaluation and Training Development: Analysis of Influencing from the Perspective of Employees. Masters thesis, Dublin, National College of Ireland.

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Abstract

With the widespread application of artificial intelligence (AI) in human resources (HR), its use in key areas such as performance management (PM) and training and development (TD) has been increasing. However, research on the differences in employees' acceptance in different application scenarios and its influencing factors is still relatively limited. This study, from the perspective of employees, comparatively analyses the differences in acceptance between the PM and TD scenarios and explores the key factors influencing their acceptance. The research adopted a quantitative research methodology, a total of 89 valid samples were collected from employed participants through a questionnaire survey, and statistical analysis methods were employed to analyses the data and present the results. The research results show that employees' acceptance of both scenarios is at a relatively high level, with the acceptance of TD slightly higher than that of PM. The key factors influencing acceptance also vary in different scenarios. In PM scenario, perceived efficiency is the strongest influencing factor, and the lack of interpersonal communication has a positive impact on acceptance. In TD, company support and transparent recommendations are key influencing factors. The findings of this study enrich the research application of AI technology acceptance models in the HR field and provide practical references for enterprises to introduce AI in different HR scenarios.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Rossiter, Elaine UNSPECIFIED
Uncontrolled Keywords:	Artificial Intelligence; Human Research Management; Performance Management; Training Development; Employee acceptance
Subjects:	Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management > Human Resource Management H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management > Human Resource Management > Training and Development
Divisions:	School of Business (- 2025) > Master of Arts in Human Resource Management
Depositing User:	Ciara O'Brien
Date Deposited:	01 Dec 2025 15:26
Last Modified:	01 Dec 2025 15:26
URI:	https://norma.ncirl.ie/id/eprint/9004

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