{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T14:37:32Z","timestamp":1777991852641,"version":"3.51.4"},"reference-count":86,"publisher":"Emerald","issue":"2","license":[{"start":{"date-parts":[[2023,11,7]],"date-time":"2023-11-07T00:00:00Z","timestamp":1699315200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["ITP"],"published-print":{"date-parts":[[2025,3,14]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>This study aims to investigate the configurational effects of five rules \u2013 artificial intelligence (AI)-based hiring decision transparency, consistency, voice, explainability and human involvement \u2013 on applicants' procedural justice perception (APJP) and applicants' interactional justice perception (AIJP). In addition, this study examines whether the identified configurations could further enhance applicants' organisational commitment (OC).<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>Drawing on the justice model of applicants' reactions, the authors conducted a longitudinal survey of 254 newly recruited employees from 36 Chinese companies that utilise AI in their hiring. The authors employed fuzzy-set qualitative comparative analysis (fsQCA) to determine which configurations could improve APJP and AIJP, and the authors used propensity score matching (PSM) to analyse the effects of these configurations on OC.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>The fsQCA generates three patterns involving five configurations that could improve APJP and AIJP. For pattern 1, when AI-based recruitment with high interpersonal rule (AI human involvement) aims for applicants' justice perception (AJP) through the combination of high informational rule (AI explainability) and high procedural rule (AI voice), there must be high levels of AI consistency and AI voice to complement AI explainability, and only this pattern of configurations can further enhance OC. In pattern 2, for the combination of high informational rule (AI explainability) and low procedural rule (absent AI voice), AI recruitment with high interpersonal rule (AI human involvement) should focus on AI transparency and AI explainability rather than the implementation of AI voice. In pattern 3, a mere combination of procedural rules could sufficiently improve AIJP.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>This study, which involved real applicants, is one of the few empirical studies to explore the mechanisms behind the impact of AI hiring decisions on AJP and OC, and the findings may inform researchers and managers on how to best utilise AI to make hiring decisions.<\/jats:p><\/jats:sec>","DOI":"10.1108\/itp-04-2022-0271","type":"journal-article","created":{"date-parts":[[2023,11,6]],"date-time":"2023-11-06T08:37:47Z","timestamp":1699259867000},"page":"553-581","source":"Crossref","is-referenced-by-count":10,"title":["The configurational effects of artificial intelligence-based hiring decisions on applicants' justice perception and organisational commitment"],"prefix":"10.1108","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1740-4135","authenticated-orcid":false,"given":"Jun","family":"Yu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3674-0815","authenticated-orcid":false,"given":"Zhengcong","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lin","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","published-online":{"date-parts":[[2023,11,7]]},"reference":[{"issue":"4","key":"key2025031312453296500_ref001","doi-asserted-by":"publisher","first-page":"399","DOI":"10.1111\/ijsa.12306","article-title":"Justice perceptions of artificial intelligence in selection","volume":"28","year":"2020","journal-title":"International Journal of Selection and Assessment"},{"key":"key2025031312453296500_ref002","doi-asserted-by":"publisher","first-page":"52138","DOI":"10.1109\/ACCESS.2018.2870052","article-title":"Peeking inside the black-box: a survey on explainable artificial intelligence (XAI)","volume":"6","year":"2018","journal-title":"IEEE Access"},{"issue":"4","key":"key2025031312453296500_ref003","doi-asserted-by":"publisher","first-page":"841","DOI":"10.1007\/s10676-021-09619-6","article-title":"The ethical use of artificial intelligence in human resource management: a\u00a0decision-making framework","volume":"23","year":"2021","journal-title":"Ethics and Information Technology"},{"issue":"3","key":"key2025031312453296500_ref004","doi-asserted-by":"publisher","first-page":"1","DOI":"10.25035\/pad.2019.03.002","article-title":"Fair and flexible?! 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