Is Friendly Always better and Alert Always Worse? The Mechanisms of Different Styles and Alert Presence in AI Interview

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

As technology evolves, e-interviewing gains prominence for its efficiency and resource-saving benefits. Despite this, AI interviews consistently elicit negative candidate attitudes. To improve perceptions of this emerging method, we examine candidate responses to different AI interview designs. Specifically, we explore how interview style and monitoring alerts affect perceptions of organizational attractiveness and attitude to rejection. Our experiment reveals that alerts enhance both the positive relationship between a friendly interview style and organization attractiveness, as well as the negative relationship between a friendly style and attitude towards rejection, both mediated by perceived warmth and competence. These findings shed light on the impact of alerts on candidate perceptions, informing our understanding of AI interview design. They also offer practical insights for organizations employing such systems, illustrating the intricate dynamics between interview styles, alert cues, and candidate perceptions, ultimately shaping organizational attractiveness and response to rejection.
Original languageEnglish
Title of host publicationPACIS 2024 Proceedings
Publication statusPublished - Jul 2024
Event2024 Pacific Asia Conference on Information Systems (PACIS 2024): Preparing The Next Generation For The IT-Driven Future - Ho Chi Minh City, Viet Nam
Duration: 1 Jul 20245 Jul 2024
https://pacis2024.aisconferences.org/
https://aisel.aisnet.org/pacis2024/

Conference

Conference2024 Pacific Asia Conference on Information Systems (PACIS 2024)
PlaceViet Nam
CityHo Chi Minh City
Period1/07/245/07/24
Internet address

Bibliographical note

Research Unit(s) information for this publication is provided by the author(s) concerned.

Funding

The work described in this paper was fully supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. CityU 11500421).

Research Keywords

  • AI interview
  • Interview style
  • Alert
  • Warmth
  • Competence

RGC Funding Information

  • RGC-funded

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