IDEAS home Printed from https://ideas.repec.org/a/gam/jchals/v10y2019i2p35-d254781.html
   My bibliography  Save this article

Challenges in Recruitment and Selection Process: An Empirical Study

Author

Listed:
  • Sophia Diana Rozario

    (La Trobe Business School, La Trobe University, Melbourne 3086, Australia)

  • Sitalakshmi Venkatraman

    (Department of Information Technology, Melbourne Polytechnic, Melbourne 3072, Australia)

  • Adil Abbas

    (Holmesglen Institute, Southbank VIC 3006, Australia)

Abstract

Today’s knowledge economy very much depends on the value created by the human resource of an organisation. In such a highly competitive environment, organisations have started to pay much attention to the recruitment and selection process, as employees form their main asset. However, the critical factors involved in the employee selection process is not well studied. Previous studies on the recruitment and selection process have been performed mainly to study the performance of the employees and the criteria attracting the right talent leading to employee retention and organizational efficiency. The distinction of this paper is that it studies the existing recruitment and selection process adopted by tertiary and dual education sectors in both urban and regional areas within Australia. The purpose of this research is to conduct an empirical study to identify the critical aspects of the employee selection process that can influence the decision based on different perspectives of the participants such as, hiring members, successful applicants as well as unsuccessful applicants. Various factors such as feedback provision, interview panel participation and preparations, relevance of interview questions, duration and bias were analysed, and their correlations were studied to gain insights in providing suitable recommendations for enhancing the process.

Suggested Citation

  • Sophia Diana Rozario & Sitalakshmi Venkatraman & Adil Abbas, 2019. "Challenges in Recruitment and Selection Process: An Empirical Study," Challenges, MDPI, vol. 10(2), pages 1-22, August.
  • Handle: RePEc:gam:jchals:v:10:y:2019:i:2:p:35-:d:254781
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2078-1547/10/2/35/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2078-1547/10/2/35/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    Full references (including those not matched with items on IDEAS)

    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.
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. repec:cup:judgdm:v:8:y:2013:i:5:p:512-520 is not listed on IDEAS
    15. 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).
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.

    Corrections

    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.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.