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Purpose

The technological evolution of job interviews continues as highly automated interviews emerge as alternative approaches. Initial evidence shows that applicants react negatively to such interviews. Additionally, there is emerging evidence that contextual influences matter when investigating applicant reactions to highly automated interviews. However, previous research has ignored higher-level organizational contexts (i.e. which kind of organization uses the selection procedure) and individual differences (e.g. work experience) regarding applicant reactions. The purpose of this paper is to investigate applicant reactions to highly automated interviews for students and employees and the role of the organizational context when using such interviews.

Design/methodology/approach

In a 2 × 2 online study, participants read organizational descriptions of either an innovative or an established organization and watched a video displaying a highly automated or a videoconference interview. Afterwards, participants responded to applicant reaction items.

Findings

Participants (n=148) perceived highly automated interviews as more consistent but as conveying less social presence. The negative effect on social presence diminished organizational attractiveness. The organizational context did not affect applicant reactions to the interview approaches, whereas differences between students and employees emerged but only affected privacy concerns to the interview approaches.

Research limitations/implications

The organizational context seems to have negligible effects on applicant reactions to technology-enhanced interviews. There were only small differences between students and employees regarding applicant reactions.

Practical implications

In a tense labor market, hiring managers need to be aware of a trade-off between efficiency and applicant reactions regarding technology-enhanced interviews.

Originality/value

This study investigates high-level contextual influences and individual differences regarding applicant reactions to highly automated interviews.

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