(In)human decisions: algorithms, employee emotions, attitudes and behavior

Sarah Hudson and Helena González-Gómez
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Sarah Hudson: Rennes SB - Rennes School of Business
Helena González-Gómez: NEOMA - Neoma Business School

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Abstract: Algorithms are becoming Human Resource (HR) decision-makers at work, yet our understanding of their impact on employee emotions, attitudes and behaviour is still limited. Prior research has focused on characteristics of the system, and cognitive assessments such as justice or trust. Using appraisal theory our paper examines emotional reactions to algorithmic versus human HR decisions to explore how these differ in terms of their effects on job satisfaction, organizational citizenship behaviour (OCB) and workplace deviance. Results from four vignette experiments with working adults (N = 1,745) reveal that in HR decisions, the decision-maker; (algorithm versus human) only affects employee attitudes and behaviour in conditions of high goal relevance and unfavourableness for the employee. The mechanism for this effect is justice perceptions and anger. Further, appraisals of uncertainty and control affect employee justice perceptions, anger and employee outcomes irrespective of the decision-maker. Our results contest the assumption that technology is imbued with opacity and unpredictability, showing that human-led processes can be perceived in a similar way. We discuss implications for theory and practice.

Keywords: Algorithmic decisions; anger; appraisal theory (search for similar items in EconPapers)
Date: 2026-02-10
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Published in European Journal of Work and Organizational Psychology, 2026, 35 (5), pp.525-542. ⟨10.1080/1359432X.2026.2628002⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05770675

DOI: 10.1080/1359432X.2026.2628002

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