First Impressions by Machine: Candidates’ Perceptions of Ethics and Employer Image in AI Recruitment Process
Purpose – The aim of this research is to investigate the impact of perceived usefulness of AI recruitment processes (PU-AIRP) on candidate perceptions of utility (PUT), fairness (PF), and privacy (PP), and how these factors influence organizational attractiveness (OA). It further examines the mediat...
محفوظ في:
| المؤلف الرئيسي: | |
|---|---|
| التنسيق: | masterThesis |
| منشور في: |
2025
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| الوصول للمادة أونلاين: | http://hdl.handle.net/10725/16975 https://doi.org/10.26756/th.2023.774 http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.php |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
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| _version_ | 1864513473619165184 |
|---|---|
| author | Al Moghrabi, Abdul Rahman |
| author_facet | Al Moghrabi, Abdul Rahman |
| author_role | author |
| dc.creator.none.fl_str_mv | Al Moghrabi, Abdul Rahman |
| dc.date.none.fl_str_mv | 2025-06-16T07:05:09Z 2025-06-16T07:05:09Z 2025 2025-05-19 |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10725/16975 https://doi.org/10.26756/th.2023.774 http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.php |
| dc.language.none.fl_str_mv | en |
| dc.publisher.none.fl_str_mv | Lebanese American University |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.title.none.fl_str_mv | First Impressions by Machine: Candidates’ Perceptions of Ethics and Employer Image in AI Recruitment Process |
| dc.type.none.fl_str_mv | Thesis info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/masterThesis |
| description | Purpose – The aim of this research is to investigate the impact of perceived usefulness of AI recruitment processes (PU-AIRP) on candidate perceptions of utility (PUT), fairness (PF), and privacy (PP), and how these factors influence organizational attractiveness (OA). It further examines the mediating roles of PF, PP, and PUT, and explores whether candidate experience with AI recruitment (E-AIRP) moderates the relationship between PU-AIRP and PUT. Design/methodology/approach – A quantitative methodology was employed using an online survey targeting job seekers and employees with exposure to AI-based recruitment tools such as applicant tracking systems (ATS), chatbots, or automated screening. Data were collected in early 2025, yielding 221 valid responses from participants across Lebanon, the GCC, Europe, and the United States. Structural relationships were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4, assessing both direct and indirect effects, as well as the moderating role of experience. Findings – The results show that PU-AIRP positively influences candidates’ perceptions of fairness and PUT but negatively affects PP. Fairness and utility significantly contribute to OA, while privacy does not. Additionally, candidates with E-AIRP strengthens the positive relationship between PU-AIRP and PUT but has no direct effect. Mediation analysis confirms that fairness and utility serve as key intermediaries in shaping candidate perceptions, while privacy does not. Research limitations/implications – Although the study is limited to a cross-sectional sample and self-reported data, it offers valuable insights into how candidates form ethical and practical evaluations of AI in recruitment. It supports organizations in designing AI hiring systems that balance efficiency with fairness, transparency, and candidate trust. Originality/value – This research contributes to the growing literature on AI ethics in HR by integrating both utilitarian and deontological perspectives into a single candidate-centered framework. It is among the first to model fairness, privacy, and utility as mediators in AI recruiting perceptions while testing the moderating influence of prior experience. |
| eu_rights_str_mv | openAccess |
| format | masterThesis |
| id | LAURepo_f81b4e32d66c268a68d40c59f8d00658 |
| language_invalid_str_mv | en |
| network_acronym_str | LAURepo |
| network_name_str | Lebanese American University repository |
| oai_identifier_str | oai:laur.lau.edu.lb:10725/16975 |
| publishDate | 2025 |
| publisher.none.fl_str_mv | Lebanese American University |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | First Impressions by Machine: Candidates’ Perceptions of Ethics and Employer Image in AI Recruitment ProcessAl Moghrabi, Abdul RahmanPurpose – The aim of this research is to investigate the impact of perceived usefulness of AI recruitment processes (PU-AIRP) on candidate perceptions of utility (PUT), fairness (PF), and privacy (PP), and how these factors influence organizational attractiveness (OA). It further examines the mediating roles of PF, PP, and PUT, and explores whether candidate experience with AI recruitment (E-AIRP) moderates the relationship between PU-AIRP and PUT. Design/methodology/approach – A quantitative methodology was employed using an online survey targeting job seekers and employees with exposure to AI-based recruitment tools such as applicant tracking systems (ATS), chatbots, or automated screening. Data were collected in early 2025, yielding 221 valid responses from participants across Lebanon, the GCC, Europe, and the United States. Structural relationships were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4, assessing both direct and indirect effects, as well as the moderating role of experience. Findings – The results show that PU-AIRP positively influences candidates’ perceptions of fairness and PUT but negatively affects PP. Fairness and utility significantly contribute to OA, while privacy does not. Additionally, candidates with E-AIRP strengthens the positive relationship between PU-AIRP and PUT but has no direct effect. Mediation analysis confirms that fairness and utility serve as key intermediaries in shaping candidate perceptions, while privacy does not. Research limitations/implications – Although the study is limited to a cross-sectional sample and self-reported data, it offers valuable insights into how candidates form ethical and practical evaluations of AI in recruitment. It supports organizations in designing AI hiring systems that balance efficiency with fairness, transparency, and candidate trust. Originality/value – This research contributes to the growing literature on AI ethics in HR by integrating both utilitarian and deontological perspectives into a single candidate-centered framework. It is among the first to model fairness, privacy, and utility as mediators in AI recruiting perceptions while testing the moderating influence of prior experience.Lebanese American University2025-06-16T07:05:09Z2025-06-16T07:05:09Z20252025-05-19Thesisinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesishttp://hdl.handle.net/10725/16975https://doi.org/10.26756/th.2023.774http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.phpeninfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/169752025-06-16T10:05:40Z |
| spellingShingle | First Impressions by Machine: Candidates’ Perceptions of Ethics and Employer Image in AI Recruitment Process Al Moghrabi, Abdul Rahman |
| status_str | publishedVersion |
| title | First Impressions by Machine: Candidates’ Perceptions of Ethics and Employer Image in AI Recruitment Process |
| title_full | First Impressions by Machine: Candidates’ Perceptions of Ethics and Employer Image in AI Recruitment Process |
| title_fullStr | First Impressions by Machine: Candidates’ Perceptions of Ethics and Employer Image in AI Recruitment Process |
| title_full_unstemmed | First Impressions by Machine: Candidates’ Perceptions of Ethics and Employer Image in AI Recruitment Process |
| title_short | First Impressions by Machine: Candidates’ Perceptions of Ethics and Employer Image in AI Recruitment Process |
| title_sort | First Impressions by Machine: Candidates’ Perceptions of Ethics and Employer Image in AI Recruitment Process |
| url | http://hdl.handle.net/10725/16975 https://doi.org/10.26756/th.2023.774 http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.php |