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Service employees’ appraisals toward artificial intelligence, robotics and automation in the workplace – results of exploratory and confirmatory factor analyses

发表年份
2025
引用次数
2
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摘要

Purpose: In view of the rapid advancements in artificial intelligence, robotics, and automation (AIRA) within service industries, it is crucial to understand how these technologies are perceived by organizational members to ensure their effective implementation.Therefore, the purpose of this paper is to gain insights into employees' appraisals toward AIRA in the workplace in service settings.Design/methodology/approach: A quantitative approach was adopted, with data being collected via a self-administered online survey from 369 service employees in Poland.The sample was randomly split into two subsamples.The first subsample was used for exploratory factor analysis (EFA), while the second subsample was used for confirmatory factor analysis (CFA).Findings: The results of the EFA and CFA indicate that the AIRA appraisal scale is multidimensional and consists of three subscales: resource appraisal toward AIRA, challenge appraisal toward AIRA, and hindrance appraisal toward AIRA.AIRA in the workplace is perceived by service employees predominantly as a resource, then as a challenge, and lastly as a hindrance.Research limitations/implications: The data collection was based on the non-random sampling technique and the questionnaire was disseminated among employees of selected service industries in Poland, which limits the generalizability of the findings beyond the specific context of this research.Originality/value: Drawing upon the refined job demands-resources (JD-R) model, the study provides a comprehensive and nuanced perspective on employees' perceptions of AIRA integration into service delivery processes.The proposed perspective is better suited to explain employees' attitudinal and behavioral reactions to AIRA-driven changes in the work environment.

关键词

Confirmatory factor analysisRoboticsArtificial intelligenceAutomationService (business)Exploratory factor analysisPsychologyApplied psychologyComputer scienceKnowledge management

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