Challenges in Recruitment and Selection Process: An Empirical Study
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Highhouse, Scott, 2008. "Stubborn Reliance on Intuition and Subjectivity in Employee Selection," Industrial and Organizational Psychology, Cambridge University Press, vol. 1(3), pages 333-342, September.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Markus Jung & Mischa Seiter, 2021. "Towards a better understanding on mitigating algorithm aversion in forecasting: an experimental study," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 32(4), pages 495-516, December.
- Kausel, Edgar E. & Culbertson, Satoris S. & Madrid, Hector P., 2016. "Overconfidence in personnel selection: When and why unstructured interview information can hurt hiring decisions," Organizational Behavior and Human Decision Processes, Elsevier, vol. 137(C), pages 27-44.
- Benedikt Berger & Martin Adam & Alexander Rühr & Alexander Benlian, 2021. "Watch Me Improve—Algorithm Aversion and Demonstrating the Ability to Learn," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(1), pages 55-68, February.
- Dalton, Michael & Landry, Peter, 2020. "‘Overattention’ to first-hand experience in hiring decisions: Evidence from professional basketball," Journal of Economic Behavior & Organization, Elsevier, vol. 175(C), pages 98-113.
- Monika Kackovic & Joop Hartog & Hans van Ophem & Nachoem Wijnberg, 2022. "The promise of potential: A study on the effectiveness of jury selection to a prestigious visual arts program," Kyklos, Wiley Blackwell, vol. 75(3), pages 410-435, August.
- Palmeira, Mauricio, 2020. "Advice in the presence of external cues: The impact of conflicting judgments on perceptions of expertise," Organizational Behavior and Human Decision Processes, Elsevier, vol. 156(C), pages 82-96.
- Brice Corgnet, 2023.
"An Experimental Test of Algorithmic Dismissals,"
Working Papers
2302, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
- Brice Corgnet, 2023. "An Experimental Test of Algorithmic Dismissals," Working Papers 23-02, Chapman University, Economic Science Institute.
- Szeli, Leon, 2020. "UX in AI: Trust in Algorithm-based Investment Decisions," Junior Management Science (JUMS), Junior Management Science e. V., vol. 5(1), pages 1-18.
- Zulia Gubaydullina & Jan René Judek & Marco Lorenz & Markus Spiwoks, 2022. "Comparing Different Kinds of Influence on an Algorithm in Its Forecasting Process and Their Impact on Algorithm Aversion," Businesses, MDPI, vol. 2(4), pages 1-23, October.
- Abdul Waheed & Jianhua Yang, 2019. "Effect of Prejudice and References on Employee Selection Process: Empirical Evidence from Pakistan," Global Business Review, International Management Institute, vol. 20(6), pages 1344-1360, December.
- Yael Karlinsky-Shichor & Oded Netzer, 2024. "Automating the B2B Salesperson Pricing Decisions: A Human-Machine Hybrid Approach," Marketing Science, INFORMS, vol. 43(1), pages 138-157, January.
- Dargnies, Marie-Pierre & Hakimov, Rustamdjan & Kübler, Dorothea, 2022.
"Aversion to hiring algorithms: Transparency, gender profiling, and self-confidence,"
Discussion Papers, Research Unit: Market Behavior
SP II 2022-202, WZB Berlin Social Science Center.
- Marie-Pierre Dargnies & Rustamdjan Hakimov & Dorothea Kübler, 2022. "Aversion to Hiring Algorithms: Transparency, Gender Profiling, and Self-Confidence," CESifo Working Paper Series 9968, CESifo.
- Dargnies, Marie-Pierre & Hakimov, Rustamdjan & Kübler, Dorothea, 2022. "Aversion to Hiring Algorithms: Transparency, Gender Profiling, and Self-Confidence," Rationality and Competition Discussion Paper Series 334, CRC TRR 190 Rationality and Competition.
- Marie-Pierre Dargnies & Rustamdjan Hakimov & Dorothee Kübler, 2023. "Aversion to hiring algorithms: Transparency, gender profiling, and self-confidence," Post-Print hal-04413060, HAL.
- Lai, Yi-Ling & Ishizaka, Alessio, 2020. "The application of multi-criteria decision analysis methods into talent identification process: A social psychological perspective," Journal of Business Research, Elsevier, vol. 109(C), pages 637-647.
- repec:cup:judgdm:v:8:y:2013:i:5:p:512-520 is not listed on IDEAS
- Nørskov, Sladjana & Damholdt, Malene F. & Ulhøi, John P. & Jensen, Morten Berg & Mathiasen, Mia Krogager & Ess, Charles M. & Seibt, Johanna, 2022. "Employers’ and applicants’ fairness perceptions in job interviews: using a teleoperated robot as a fair proxy," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
- Chiara Longoni & Andrea Bonezzi & Carey K Morewedge, 2019. "Resistance to Medical Artificial Intelligence," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 46(4), pages 629-650.
- Sima Wolgast & Martin Bäckström & Fredrik Björklund, 2017. "Tools for fairness: Increased structure in the selection process reduces discrimination," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-15, December.
- Woolley, Kaitlin & Fishbach, Ayelet, 2018. "Underestimating the importance of expressing intrinsic motivation in job interviews," Organizational Behavior and Human Decision Processes, Elsevier, vol. 148(C), pages 1-11.
- Martin Bäckström & Fredrik Björklund, 2017. "Increasing systematicity leads to better selection decisions: Evidence from a computer paradigm for evaluating selection tools," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-15, May.
- Kappes, Heather Barry & Balcetis, Emily & De Cremer, David, 2018. "Motivated reasoning during recruitment," LSE Research Online Documents on Economics 84093, London School of Economics and Political Science, LSE Library.
- Sharps, Daron L. & Anderson, Cameron, 2021. "Social class background, disjoint agency, and hiring decisions," Organizational Behavior and Human Decision Processes, Elsevier, vol. 167(C), pages 129-143.
More about this item
Keywords
human resource; recruitment and selection process; critical factors; interview bias; feedback; stakeholder perspectives; education sector;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jchals:v:10:y:2019:i:2:p:35-:d:254781. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.