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The implications and impact of artificial intelligence, big data and HR analytics in HRM: A critical analysis of EU enterprises

KIU, CHUN,TUNG,THOMAS (2023) The implications and impact of artificial intelligence, big data and HR analytics in HRM: A critical analysis of EU enterprises. Doctoral thesis, Durham University.

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This study offers a critical evaluation of HR analytics. Specifically, the ideas and concepts surrounding HR analytics, such as what is HR analytics, the development of HR analytics in organizations and how it may impact organizational performance. To advance and answer these research questions, this study relied on systematic reviews, logistic regression, interaction effect analysis, and interviews with the European Company Survey (ECS) to assess the interrelationship between HR analytics and organizational factors. Based on the findings, certain key areas are addressed. Firstly, research question 1 has succeeded in developing a more systematic and coherent definition of HR analytics and artificial intelligence in HR. It has also successfully identified some factors that influence the use of HR analytics in organisations. In particular, the results of study two found that factors such as firm age, firm size, the complexity of the firm process and the type of variable pay systems have been shown to be key indicators of why certain companies use HR analytics while others do not. Furthermore, the results for study three also provided a bigger picture of how organizational factors might be the reasons for explaining firms’ financial returns when examining the relationship between variables. In particular, factors such as employee motivation, the use of HR analytics, and variable pay systems are also believed to be critical in determining which factors affect a company’s financial returns. In addition, the study provides additional knowledge for five specific areas in analytics and artificial intelligence in HR, namely firm characteristics, challenges, key reasons to adopt HR software, new trends and user traits.

Item Type:Thesis (Doctoral)
Award:Doctor of Philosophy
Keywords:artificial intelligence, big data, HR analytics, human resource management, HRM, People analytics, human resource analytics
Faculty and Department:Faculty of Business > Management and Marketing, Department of
Thesis Date:2023
Copyright:Copyright of this thesis is held by the author
Deposited On:20 Feb 2023 10:36

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