Highly automated job interviews: Acceptance under the influence of stakes
Open accessAbstract
Technological advancements allow the automation of every part of job interviews (information acquisition, information analysis, action selection, action implementation) resulting in highly automated interviews. Efficiency advantages exist, but it is unclear how people react to such interviews (and whether reactions depend on the stakes involved). Participants ( N = 123) in a 2 (highly automated, videoconference) × 2 (high‐stakes, low‐stakes situation) experiment watched and assessed videos depicting a highly automated interview for high‐stakes (selection) and low‐stakes (training) situations or an equivalent videoconference interview. Automated high‐stakes interviews led to ambiguity and less perceived controllability. Additionally, highly automated interviews diminished overall acceptance through lower social presence and fairness. To conclude, people seem to react negatively to highly automated interviews and acceptance seems to vary based on the stakes. Open Practices: This study was pre‐registered on the Open Science Framework ( osf.io/hgd5r ) and on AsPredicted ( https://AsPredicted.org/i52c6.pdf ).
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Empirical findings on behavioral reliance on algorithmic advice remain inconsistent, with some studies reporting reluctance to use algorithmic decision aids in recruitment and others showing that recruiters continue to follow algorithmic recommendations even when they are inaccurate.
“Empirical findings on behavioral reliance on algorithmic advice remain inconsistent.Some studies report reluctance to use algorithmic decision aids in recruitment contexts (Acikgoz et al. 2020;Langer et al. 2019;Oberst et al. 2020), whereas others show that recruiters continue to follow algorithmic recommendations even when they are inaccurate (Cecil et al. 2024;Lacroux and Martin-Lacroux 2022).”
From When Recruiters Meet Algorithms: Advice Taking and Bias in AI‐Assisted Recruitment (2026) · cites this paper as Langer et al. 2019
Cites
(2013) · Cited by 44,563 · see citing works
Statistical power analyses using G∗Power 3.1: tests for correlation and regression analyses
Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009) · Behavior Research Methods · doi:10.3758/brm.41.4.1149 · Cited by 37,615 · see citing works
User Acceptance of Computer Technology: A Comparison of Two Theoretical Models
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989) · Management Science · doi:10.1287/mnsc.35.8.982 · Cited by 25,709 · see citing works
A Simple Sequentially Rejective Multiple Test Procedure
(1979) · Scandinavian Journal of Statistics · doi:10.2307/4615733 · Cited by 21,526 · see citing works
Estimating the reproducibility of psychological science
Open Science Collaboration (2015) · Science · doi:10.1126/science.aac4716 · Cited by 8,515 · see citing works
Ajzen, I. (2002) · Journal of Applied Social Psychology · doi:10.1111/j.1559-1816.2002.tb00236.x · Cited by 7,629 · see citing works
Praat, a system for doing phonetics by computer
Boersma, P. (2002) · UvA-DARE (University of Amsterdam) · Cited by 4,417 · see citing works
A model for types and levels of human interaction with automation
Parasuraman, R., Sheridan, T. B., & Wickens, C. D. (2000) · IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans · doi:10.1109/3468.844354 · Cited by 4,195 · cited 6× · see citing works
“In particular, the tool should include all aspects of highly-automated interviews: acquire information, analyze information, select and decide about potential actions, and implement these actions (Hoff & Bashir, 2015; Parasuraman et al., 2000).”
InfluentialThe Uncanny Valley [From the Field]
Mori, M., MacDorman, K., & Kageki, N. (2012) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2012.2192811 · Cited by 3,542 · see citing works
The ethics of algorithms: Mapping the debate
Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016) · Big Data & Society · doi:10.1177/2053951716679679 · Cited by 3,432 · cited 4× · see citing works
“, deep learning algorithms), providing information can become a challenge (Mittelstadt et al., 2016; Zerilli, Knott, Maclaurin, & Gavaghan, 2018).”
InfluentialInternet Users' Information Privacy Concerns (IUIPC): The Construct, the Scale, and a Causal Model
Malhotra, N. K., Kim, S. S., & Agarwal, J. (2004) · Information Systems Research · doi:10.1287/isre.1040.0032 · Cited by 3,173 · see citing works
Trust in Automation: Integrating Empirical Evidence on Factors That Influence Trust
Hoff, K. A., & Bashir, M. (2015) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720814547570 · Cited by 2,817 · see citing works
Information Privacy: Measuring Individuals’ Concerns About Organizational Practices1
Smith, H. J., Milberg, S. J., & Burke, S. J. (1996) · MIS Quarterly · doi:10.2307/249477 · Cited by 2,266 · see citing works
Nass, C., Steuer, J., & Tauber, E. R. (1994) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/191666.191703 · Cited by 2,148 · see citing works
Construction and Evaluation of a User Experience Questionnaire
Laugwitz, B., Held, T., & Schrepp, M. (2008) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-89350-9_6 · Cited by 2,114 · see citing works
OpenFace: An open source facial behavior analysis toolkit
Baltrušaitis, T., Robinson, P., & Morency, L. (2016) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv.2016.7477553 · Cited by 1,771 · see citing works
From visual simulation to virtual reality to games
Zyda, M. (2005) · Computer · doi:10.1109/mc.2005.297 · Cited by 1,472 · see citing works
Bukimi no tani [the uncanny valley]
Mori, M. (1970) · Energy · Cited by 1,457 · see citing works
Lee, M. K. (2018) · Big Data & Society · doi:10.1177/2053951718756684 · Cited by 1,338 · see citing works
The Perceived Fairness of Selection Systems: An Organizational Justice Perspective
Gilliland, S. W. (1993) · The Academy of Management Review · doi:10.2307/258595 · Cited by 1,185 · see citing works
Experimental Vignette Studies in Survey Research
Atzmüller, C., & Steiner, P. M. (2010) · Methodology · doi:10.1027/1614-2241/a000014 · Cited by 1,049 · see citing works
A META‐ANALYTIC EXAMINATION OF THE INSTRUCTIONAL EFFECTIVENESS OF COMPUTER‐BASED SIMULATION GAMES
SITZMANN, T. (2011) · Personnel Psychology · doi:10.1111/j.1744-6570.2011.01190.x · Cited by 882 · see citing works
Measuring Attraction to Organizations
Highhouse, S., Lievens, F., & Sinar, E. F. (2003) · Educational and Psychological Measurement · doi:10.1177/0013164403258403 · Cited by 855 · see citing works
Applicant Reactions to Selection Procedures: An Updated Model and Meta‐Analysis
Hausknecht, J. P., Day, D. V., & Thomas, S. C. (2004) · Personnel Psychology · doi:10.1111/j.1744-6570.2004.00003.x · Cited by 816 · see citing works
'It's Reducing a Human Being to a Percentage': Perceptions of Justice in Algorithmic Decisions
Binns, R., Van Kleek, M., Veale, M., Lyngs, U., Zhao, J., & Shadbolt, N. (2018) · Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3173951 · Cited by 691 · cited 4× · see citing works
“It seems possible that participants might have interpreted that a computer gains decision power over a human being, which may be seen as less fair than a person being in charge of conducting high-stake interviews and making high-stake selection decisions (Binns et al., 2018; M. K. Lee, 2018; Ötting & Maier, 2018).”
InfluentialThe influence of technology on the future of human resource management
Stone, D. L., Deadrick, D. L., Lukaszewski, K. M., & Johnson, R. (2015) · Human Resource Management Review · doi:10.1016/j.hrmr.2015.01.002 · Cited by 618 · see citing works
Kätsyri, J., Förger, K., Mäkäräinen, M., & Takala, T. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.00390 · Cited by 500 · see citing works
Ryan, A. M., & Ployhart, R. E. (2000) · Journal of Management · doi:10.1177/014920630002600308 · Cited by 483 · see citing works
Mori, M. (2020) · University of Minnesota Press eBooks · doi:10.5749/j.ctvtv937f.7 · Cited by 438 · see citing works
Barrick, M. R., Shaffer, J. A., & DeGrassi, S. W. (2009) · Journal of Applied Psychology · doi:10.1037/a0016532 · Cited by 431 · see citing works
Transparency in Algorithmic and Human Decision-Making: Is There a Double Standard?
Zerilli, J., Knott, A., Maclaurin, J., & Gavaghan, C. (2019) · Philosophy & Technology · doi:10.1007/s13347-018-0330-6 · Cited by 420 · see citing works
APPLICANT REACTIONS TO SELECTION: DEVELOPMENT OF THE SELECTION PROCEDURAL JUSTICE SCALE (SPJS)
Bauer, T. N., Truxillo, D. M., Sanchez, R. J., Craig, J. M., Ferrara, P., & Campion, M. A. (2001) · Personnel Psychology · doi:10.1111/j.1744-6570.2001.tb00097.x · Cited by 414 · see citing works
McCole, P., Ramsey, E., & Williams, J. (2010) · Journal of Business Research · doi:10.1016/j.jbusres.2009.02.025 · Cited by 403 · see citing works
Uggerslev, K. L., Fassina, N. E., & Kraichy, D. (2012) · Personnel Psychology · doi:10.1111/j.1744-6570.2012.01254.x · Cited by 391 · see citing works
Justice, Fairness, and Employee Reactions
Colquitt, J. A., & Zipay, K. P. (2015) · Annual Review of Organizational Psychology and Organizational Behavior · doi:10.1146/annurev-orgpsych-032414-111457 · Cited by 339 · see citing works
Soft Ethics and the Governance of the Digital
Floridi, L. (2018) · Philosophy & Technology · doi:10.1007/s13347-018-0303-9 · Cited by 325 · see citing works
Measuring Job Interview Anxiety: Beyond Weak Knees and Sweaty Palms
McCarthy, J. M., & Goffin, R. D. (2004) · Personnel Psychology · doi:10.1111/j.1744-6570.2004.00002.x · Cited by 262 · see citing works
Designing social presence of social actors in human computer interaction
Lee, K. M., & Nass, C. (2003) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/642611.642662 · Cited by 257 · see citing works
Confronting Perpetrators of Prejudice: The Inhibitory Effects of Social Costs
Nicole, S. J., & Stewart, R. E. (2004) · Psychology of Women Quarterly · doi:10.1111/j.1471-6402.2004.00138.x · Cited by 221 · see citing works
A Model of Faking Likelihood in the Employment Interview
Levashina, J., & Campion, M. A. (2006) · International Journal of Selection and Assessment · doi:10.1111/j.1468-2389.2006.00353.x · Cited by 220 · see citing works
Tapping the grapevine: A closer look at word-of-mouth as a recruitment source.
Hoye, G. V., & Lievens, F. (2009) · Journal of Applied Psychology · doi:10.1037/a0014066 · Cited by 220 · see citing works
The Usefulness of Unit Weights in Creating Composite Scores
Bobko, P., Roth, P. L., & Buster, M. A. (2007) · Organizational Research Methods · doi:10.1177/1094428106294734 · Cited by 195 · see citing works
An integrated e‐recruitment system for automated personality mining and applicant ranking
Faliagka, E., Tsakalidis, A., & Tzimas, G. E. (2012) · Internet Research · doi:10.1108/10662241211271545 · Cited by 176 · see citing works
The social signal interpretation (SSI) framework
Wagner, J., Lingenfelser, F., Baur, T., Damian, I., Kistler, F., & André, E. (2013) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/2502081.2502223 · Cited by 174 · see citing works
Technology in the Employment Interview: A Meta-Analysis and Future Research Agenda
Blacksmith, N., Willford, J. C., & Behrend, T. S. (2016) · Personnel Assessment and Decisions · doi:10.25035/pad.2016.002 · Cited by 174 · see citing works
Automated Analysis and Prediction of Job Interview Performance
Naim, I., Tanveer, M. I., Gildea, D., & Hoque, M. E. (2016) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2016.2614299 · Cited by 162 · see citing works
Ötting, S. K., & Maier, G. W. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.07.022 · Cited by 157 · see citing works
Examining digital interviews for personnel selection: Applicant reactions and interviewer ratings
Langer, M., König, C. J., & Krause, K. (2017) · International Journal of Selection and Assessment · doi:10.1111/ijsa.12191 · Cited by 150 · see citing works
Self-citationThe datafication of talent: how technology is advancing the science of human potential at work
Chamorro‐Premuzic, T., Akhtar, R., Winsborough, D., & Sherman, R. A. (2017) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2017.04.007 · Cited by 146 · see citing works
Applicant reactions to face-to-face and technology-mediated interviews: A field investigation.
Chapman, D. S., Uggerslev, K. L., & Webster, J. (2003) · Journal of Applied Psychology · doi:10.1037/0021-9010.88.5.944 · Cited by 143 · see citing works
The Medium and the Message: The Adaptive Use of Communication Media in Dyadic Influence
Barry, B., & Fulmer, I. S. (2004) · Academy of Management Review · doi:10.5465/amr.2004.12736093 · Cited by 142 · see citing works
Lee, S. M., Kim, Y. R., & Lee, J. (1995) · Journal of Management Information Systems · doi:10.1080/07421222.1995.11518086 · Cited by 136 · see citing works
A Theory of Creepy: Technology, Privacy and Shifting Social Norms
Tene, O., & Polonetsky, J. (2013) · bepress Legal Repository · Cited by 136 · see citing works
Bauer, T. N., Truxillo, D. M., Tucker, J. S., Weathers, V. M., Bertolino, M., Erdoğan, B., & Campion, M. A. (2006) · Journal of Management · doi:10.1177/0149206306289829 · Cited by 135 · see citing works
2021 IEEE Winter Conference on Applications of Computer Vision (WACV)
da Costa, V. G. T., Zara, G., Rota, P., Oliveira-Santos, T., Sebe, N., Murino, V., & Elisa, R. (2021) · doi:10.1109/wacv48630.2021 · Cited by 131 · see citing works
Initial investigation into computer scoring of candidate essays for personnel selection.
Campion, M. C., Campion, M. A., Campion, E. D., & Reider, M. H. (2016) · Journal of Applied Psychology · doi:10.1037/apl0000108 · Cited by 130 · see citing works
Langer, M., König, C. J., & Fitili, A. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2017.11.036 · Cited by 119 · see citing works
Self-citationCan Virtual Humans Be More Engaging Than Real Ones?
Gratch, J. S., Wang, N., Okhmatovskaia, A., Lamothe, F., Morales, M., van der Werf, R. J., & Morency, L. (2007) · Lecture notes in computer science · doi:10.1007/978-3-540-73110-8_30 · Cited by 110 · see citing works
Factors affecting the effectiveness and acceptance of electronic selection systems
Stone, D. L., Lukaszewski, K. M., Stone‐Romero, E. F., & Johnson, T. L. (2012) · Human Resource Management Review · doi:10.1016/j.hrmr.2012.06.006 · Cited by 106 · see citing works
Peeters, H., & Lievens, F. (2006) · International Journal of Selection and Assessment · doi:10.1111/j.1468-2389.2006.00348.x · Cited by 105 · see citing works
Patients Derogate Physicians Who Use a Computer-Assisted Diagnostic Aid
Arkes, H. R., Shaffer, V. A., & Medow, M. A. (2007) · Medical Decision Making · doi:10.1177/0272989x06297391 · Cited by 103 · see citing works
A Conceptual Framework for the Role of the Administration Medium in the Personnel Assessment Process
Potosky, D. (2008) · Academy of Management Review · doi:10.5465/amr.2008.32465704 · Cited by 100 · see citing works
Brenner, F., Ortner, T. M., & Fay, D. (2016) · Frontiers in Psychology · doi:10.3389/fpsyg.2016.00863 · Cited by 95 · see citing works
Introducing and Testing the Creepiness of Situation Scale (CRoSS)
Langer, M., & König, C. J. (2018) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.02220 · Cited by 91 · see citing works
Self-citationHolden, R. R., & Passey, J. (2010) · Personality and Individual Differences · doi:10.1016/j.paid.2010.04.015 · Cited by 86 · see citing works
A comparative assessment of videoconference and face-to-face employment interviews
Sears, G. J., Zhang, H., Wiesner, W. H., Hackett, R. D., & Yuan, Y. (2013) · Management Decision · doi:10.1108/md-09-2012-0642 · Cited by 74 · see citing works
Peck, J. A., & Levashina, J. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.00201 · Cited by 70 · see citing works
Efficient smile detection by Extreme Learning Machine
An, L., Yang, S., & Bhanu, B. (2014) · Neurocomputing · doi:10.1016/j.neucom.2014.04.072 · Cited by 68 · see citing works
Dear Computer, Teach Me Manners: Testing Virtual Employment Interview Training
Langer, M., König, C. J., Gebhard, P., & André, E. (2016) · International Journal of Selection and Assessment · doi:10.1111/ijsa.12150 · Cited by 68 · see citing works
Self-citationMaurer, T. J., Solamon, J. M., Andrews, K. D., & Troxtel, D. D. (2001) · Journal of Applied Psychology · doi:10.1037/0021-9010.86.4.709 · Cited by 65 · see citing works
Visual SceneMaker—a tool for authoring interactive virtual characters
Gebhard, P., Mehlmann, G., & Kipp, M. (2011) · Journal on Multimodal User Interfaces · doi:10.1007/s12193-011-0077-1 · Cited by 65 · see citing works
DeGroot, T., & Kluemper, D. H. (2007) · International Journal of Selection and Assessment · doi:10.1111/j.1468-2389.2007.00365.x · Cited by 59 · see citing works
Walter, N., Ortbach, K., & Niehaves, B. (2014) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2014.12.001 · Cited by 59 · see citing works
Guchait, P., Ruetzler, T., Taylor, J., & Toldi, N. (2014) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2013.08.004 · Cited by 55 · see citing works
Note-taking in the employment interview: Effects on recall and judgments.
Middendorf, C. H., & Macan, T. H. (2002) · Journal of Applied Psychology · doi:10.1037//0021-9010.87.2.293 · Cited by 51 · see citing works
Applicants’ Self-Presentational Behavior
Jansen, A., König, C. J., Stadelmann, E. H., & Kleinmann, M. (2012) · Journal of Personnel Psychology · doi:10.1027/1866-5888/a000046 · Cited by 46 · see citing works
Self-citationBuehl, A., Melchers, K. G., Macan, T. M., & Kühnel, J. (2018) · Journal of Business and Psychology · doi:10.1007/s10869-018-9531-3 · Cited by 46 · see citing works
Serious Games for Training Social Skills in Job Interviews
Gebhard, P., Schneeberger, T., André, E., Baur, T., Damian, I., Mehlmann, G., König, C. J., & Langer, M. (2018) · IEEE Transactions on Games · doi:10.1109/tg.2018.2808525 · Cited by 43 · see citing works
Self-citationSmiling in a Job Interview: When Less Is More
Ruben, M. A., Hall, J. A., & Mast, M. S. (2014) · The Journal of Social Psychology · doi:10.1080/00224545.2014.972312 · Cited by 40 · see citing works
Frauendorfer, D., Mast, M. S., Nguyen, L. S., & Gática-Pérez, D. (2014) · Journal of Nonverbal Behavior · doi:10.1007/s10919-014-0173-5 · Cited by 38 · see citing works
Using pre-test explanations to improve test-taker reactions: Testing a set of “wise” interventions
McCarthy, J. M., Bauer, T. N., Truxillo, D. M., Campion, M. C., Iddekinge, C. H. V., & Campion, M. A. (2017) · Organizational Behavior and Human Decision Processes · doi:10.1016/j.obhdp.2017.04.002 · Cited by 36 · see citing works
Nolan, K., Carter, N., & Dalal, D. (2016) · Personnel Assessment and Decisions · doi:10.25035/pad.2016.004 · Cited by 28 · see citing works
Smile Detection in the Wild Based on Transfer Learning
Guo, X., Polanía, L. F., & Barner, K. E. (2018) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fg.2018.00107 · Cited by 15 · see citing works
Research in the Era of Sensing Technologies and Wearables
Langer, M., Mast, M. S., Meyer, B. M., Maaß, W., & König, C. J. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108649636.030 · Cited by 4 · see citing works
Self-citationBinns, R., Kleek, M. G. V., Veale, M., Lyngs, U., Zhao, J., & Shadbolt, N. (2018) · UCL Discovery (University College London) · Cited by 2 · see citing works
Smile detection in the wild based on transfer learning
Guo, X., Polanía, L. F., & Barner, K. E. (2018) · arXiv · doi:10.48550/arxiv.1802.02185
Flagged first, then by citations
Research works printed but not linked: 10
- Ajzen I., 2002, Constructing a TPB questionnaire: Conceptual and methodological considerations
- Biran O., 2017, Explanation and justification in machine learning: A survey
- Boersma P., 2001, Speak and unSpeak with PRAAT, Glot International, 5, 341
- HireVue, 2018, HireVue OnDemand
- Intel, 2018, Intel RealSense technology
- 10.1037/0021-9010.87.2.293 · DOI
- Miller F. A., 2018, The OD imperative to add inclusion to the algorithms of artificial intelligence, OD Practitioner, 50, 6
- Miller T., 2017, Explainable AI: Beware of inmates running the asylum
- Precire, 2017, Precire technologies
- Warszta T, 2012, Application of Gilliland’s model of applicants’ reactions to the field of web‐based selection
Cited by
Sorted by citations
Langer, M., & Landers, R. N. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2021.106878 · Cited by 338 · see citing works
Self-citationCreepiness: Its antecedents and impact on loyalty when interacting with a chatbot
Rajaobelina, L., Prom Tep, S., Arcand, M., & Ricard, L. (2021) · Psychology & Marketing · doi:10.1002/mar.21548 · Cited by 252 · see citing works
Lee, M. K., & Rich, K. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445570 · Cited by 145 · see citing works
”Because AI is 100% right and safe”: User Attitudes and Sources of AI Authority in India
Kapania, S., Siy, O., Clapper, G., SP, A. M., & Sambasivan, N. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3517533 · Cited by 90 · see citing works
Langer, M., König, C. J., & Hemsing, V. (2020) · Journal of Managerial Psychology · doi:10.1108/jmp-03-2019-0156 · Cited by 83 · see citing works
Self-citationLacroux, A., & Martin-Lacroux, C. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.895997 · Cited by 67 · see citing works
Check the box! How to deal with automation bias in AI-based personnel selection
Kupfer, C., Prassl, R., Fleiß, J., Malin, C., Thalmann, S., & Kubicek, B. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1118723 · Cited by 59 · see citing works
“…are chatbots (e.g., Eißer et al., 2020), resume screening tools (e.g., Acikgoz et al., 2020; Noble et al., 2021), and digital, highly automated video-interview tools that evaluate speech, facial expressions, and gestures (e.g., Langer et al., 2019; Acikgoz et al., 2020; Langer et al., 2021).”
BackgroundLanger, M., Hunsicker, T., Feldkamp, T., König, C. J., & Grgić-Hlača, N. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3517527 · Cited by 55 · see citing works
Self-citationHow asynchronous video interviews are used in practice: A study of an Australian‐based AVI vendor
Dunlop, P. D., Holtrop, D., & Wee, S. (2022) · International Journal of Selection and Assessment · doi:10.1111/ijsa.12372 · Cited by 46 · see citing works
Hunkenschroer, A. (2021) · AI Ethics Journal · doi:10.47289/aiej20210716-3 · Cited by 18 · see citing works
When Recruiters Meet Algorithms: Advice Taking and Bias in AI‐Assisted Recruitment
Lacroux, A., & Martin Lacroux, C. (2026) · International Journal of Selection and Assessment · doi:10.1111/ijsa.70085
- Authors
- Langer, M., König, C. J., & Papathanasiou, M.
- Affiliations
- Saarland University (DE)
- Fachrichtung Psychologie Universität des Saarlandes Saarbrücken Germany
- Corresponding author
- Langer, Markus
- Venue
- International Journal of Selection and Assessment
- Publisher
- Wiley
- Published
- 2019-05-14
- Volume
- 27
- Issue
- 3
- Pages
- 217-234
- ISSN
- 0965-075X (ISSN-L)
- 1468-2389
- OpenAlex
- W2945982604
- Cited by
- 203
- References
- 87
- Citations by year
- 2026: 42 · 2025: 38 · 2024: 26 · 2023: 33 · 2022: 36 · 2021: 16 · 2020: 10 · 2019: 2
- FWCI
- 22.43
- Type
- journal article
- Language
- en
- Open access
- Locations
- International Journal of Selection and Assessment (publishedVersion)
- FreiDok plus (Universitätsbibliothek Freiburg) (submittedVersion)
- GoeScholar The Publication Server of the Georg-August-Universität Göttingen (Georg-August-Universität Göttingen) (submittedVersion, cc-by)
- Funders
- Bundesministerium für Bildung, Wissenschaft, Forschung und Technologie (16SV7229K)
- Topics
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Employer Branding and e-HRM
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Keywords
- acceptance of automation, perceived controllability, social presence, perceived fairness, human-automation interaction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
