Meta-analysis of employee well-being and perception towards robot, artificial intelligence, and service automation

Abstract

The implementation of smart technology has fundamentally restructured task processes and organisational optimisation. Simultaneously, its implementation presents multidimensional implications for employees, especially their well-being, while current empirical studies remain disjointed and lacks integration. A meta-analysis is considered fruitful since it provides a systematic synthesis to guide future research and delivers critical perspective for practical strategies, specifically HRM aimed at sustaining employee well-being. The objective of this meta-analysis was to investigate the correlation of employee perceptions towards robot, artificial intelligence, and service automation and their well-being, incorporating well-being conceptualisation and industry type as moderating variables. Peer-reviewed articles were retrieved from five databases, including Web of Science Scopus and EBSCOhost. Adhering the pre-determined inclusion criteria, 20 articles were statistically analyzed. The analysis conducted included effect size calculation, meta-analytic model, and heterogeneity assessment. Results revealed a significant correlation between employee perceptionsof RAISA and employee well-being. The effect size was low-to-moderate and the study heterogeneity was high. Additionally, meta-regression showed a non-significant moderating effect of industry type, yet a significant result for well-being conceptualization. This meta-analysis offers comperhensive direction for further studies, encompassing conceptual and methodological aspects, to encourage a more focused analysis on the relation between both variables.