Technology in recruitment and

selection: Past, present and the future

Ioannis NikolaouSchool of Business

MSc in Human Resources Management

twitter@Nikolaou

https://www.linkedin.com/in/ioannisnikolaou/inikol@aueb.gr

Technology in Employee Recruitment & Selection

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Recruitment

Screening

Selection

The "day after"

Technology in Recruitment

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Internet-based Recruitment

Social Networking Websites (SNWs)

Internet-based Recruitment

• Company Career Sites

– Enriched content, data and applicant tracking

• Job Boards

– Becoming more interactive, increased applicants’ attention and credibility (Nikolaou, 2014)

• Applicant Tracking Systems (ATS)

Nikolaou, I. & Tsoni, E. (in press). Internet Recruitment. In B. Warf (Ed.), The SAGE Encyclopaedia of the Internet. London: Sage.

Nikolaou, I. (2014). Social Networking Web Sites in Job Search and Employee Recruitment. International Journal of Selection and Assessment, 22(2), 179-189.

4

Internet-based Recruitment & SNWs

• Social Networking Websites (SNWs)

– A whole new world…

– A cheap and effective means of recruiting candidates, and especially approaching passive candidates / poaching (Nikolaou,

2014)

• Excessive usage numbers by both recruiters and job-seekers

• Constantly increasing research attention, but generally, an area where research still tries to catch up practice (e.g. Roulin & Levashina, 2019; Kluemper et al., 2012; Van Iddekinge et al, 2016;

Roth et al., 2013)

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Technology in Screening

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Resume Storage, Parsing, and Keyword Search

Cybervetting

Artificial Intelligence

Resume Storage, Parsing, and Keyword Search

• Large storage databases combined with ATS & candidates’ social media profiles

• Effective resume management and resume parsing tools (e.g. keyword search and profile matching)

• Data mining techniques and machine translation technologies used to elicit information on candidates

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Cybervetting

• Applicants’ screening with the use of SNWs

• Used often in combination with candidates’ info (e.g. resume, on-line application)

– Important ethical / privacy concerns and discrimination / adverse impact issues

– Limited research on how recruiters use this SNW info (especially negative/incomplete), or in combination with other info (e.g. psychometric assessment) (Nikolaou, 2014)

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Artificial Intelligence

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Web Scrapping and Linguistic Analysis-IBM Watson personality insights

twitter@nikolaou

Technology in Selection

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Digital interviewing & Voice Profiling

Automated and computer-adaptive testing

Gamification and Games-Based Assessment

Digital Interviewing & Voice Profiling

• Video-recorded structured interviews

• Benefits: increases standardization and time saving

• Limitations: lack of face-to-face interaction

– Text analytics and Voice Mining

– Algorithmic reading of voice-generated emotions

• Micro-expressions and automated emotion reading

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Automated and computer-adaptive testing

• Adaptive on-line testing

• Psychometric assessment

• Little has changed in the content, delivery

• Concerns over security conditions and administration

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Gamification and Games-Based Assessment

• Gamified Assessment

– Soft Skills assessment; 8 skills

– Highly reliable, high construct validity

– Positive applicant reactions

– Initial evidence of predictive validity

Nikolaou, I., Georgiou, K., & Kotsasarlidou, V. (in press). Exploring the relationship of a gamified assessment with performance. Spanish Journal of Psychology.

Georgiou, K., Gouras, A. & Nikolaou, I. (in press). Gamification in employee selection: The development of a gamified assessment. International Journal of Selection and Assessment.

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Technology & the “day after”

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Applicant Reactions

Employer Branding

Big Data & HR Analytics

Technology & Applicant Reactions

• Applicant reactions &

– New predictor methods (e.g. digital interviews, gamification, video CVs, etc.)

– New modes of delivery of existing predictor constructs (e.g. personality, intelligence)

– Social Networking Websites

• Impact to applicants attitudes / outcomes, compared to traditional methods/constructs?

Nikolaou, I. Georgiou, K. Bauer, T.N, Truxillo, D. M. (in press). Technology and Applicant Reactions. In R. N. Landers (Ed.). Cambridge Handbook of Technology and Employee Behavior, Cambridge University Press.

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Technology & Applicant Reactions

Process Favorability ratings (1=Least favorable, 7=Most favorable)

Traditional Methods1 Mean SD Technology-oriented methods2 Mean SD

Interview 5.32 1.20 On-line Interviews (e.g. Skype) 5.26 1.3

Work Sample 4.80 1.39 On-Line Personality Testing 4.82 1.39

Resumes/CVs 4.73 1.25 On-Line Cognitive Ability Testing 4.80 1.37

Cognitive Ability Testing 4.34 1,32 On-Line Application Forms 4.68 1.35

Biodata 4.23 1,18 Video-Based SJTs 4.62 1.38

Personality Testing 4.17 1,37 Professional Social Networking Websites 4.58 1.33

Personal References 3.86 1,39 Gamification-GBAs 4.55 1.51

Integrity Testing 3.52 1.47 Video-CVs 4.28 1.55

Personal Contacts 3.35 1.58 Digital Interviewing 4.15 1.39

Graphology 2.30 1.28 Personal Social Networking Websites 2.86 1.41

1 Nikolaou & Judge (2007) 2 Nikolaou & Lagou (in preparation)

Technology & Employer Branding

• Strong links with applicant reactions and SNWs (e.g. Glassdoor)

• Word-of-mouth vs. Word-of-mouse (WOM)

– The differential impact of Positive WOM vs Negative WOM (Van Hoye, G., 2014).

• The uncertain impact of “Best employers”& HR Awards competitions (Lievens & Slaughter, 2016)

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Big Data and HR Analytics

• Not just HR Metrics… but using advanced statistical methods and combining HR with business data

– Data Mining

• Combining internal and external data

– For example:

• Predicting hiring success & high potentials

• Reducing turnover and increasing employee engagement and satisfaction– Using data from both internal and external sources 18

Critical issues 1/2

• Ethics

– Applicants’ consent

– Confidentiality

• Legal considerations

– Data privacy and data protection

– Test Security

• Equivalence of measures / techniquesShen, W., Sackett, P.R., Nikolaou, I., et al. (2017). Updated Perspectives on the International Legal Environment for Selection. In

J. L Farr and N. T. Tippins (Eds.) Handbook of Employee Selection (pp. 659-677). New York: Taylor & Francis.

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Critical issues 2/2

• Bandwidth vs. fidelity

• Implementation, administration issues (e.g. mobile devices, tablets) and cost development

• Un-proctored assessment in high stakes selection

• Predictor constructs (e.g., personality, cognitive ability) vs. predictor methods (e.g., video résumés, digital interviews)

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The future is here, but… (1/2)

• Vast data pools and improved analytic capabilities will fundamentally disrupt the talent identification process.

– Availability of many more talent signals

– New analytic tools and increased computing power

However…

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The future is here, but… (2/2)

• Limited validity evidence compared to old school methods

• Privacy and anonymity concerns may limit access to individual data

• Trade-off between development costs and accuracy/validity and user experience

• Adverse impact / unfair discrimination concerns

Chamorro-Premuzic, T., Winsborough, D., Sherman, R. A., & Hogan, R. (2016). New Talent Signals: Shiny New Objects or a Brave New World? Industrial and Organizational Psychology-Perspectives on Science and Practice, 9(3), 621-640.

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Conclusions

• We live our lives online (and so do recruiters) but…

Valid, evidence-based tools and methodologies are required in order to take fair and just hiring

decisions

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Ioannis NikolaouSchool of Business

Department of Management Science & Technology

twitter@nikolaouinikolaou.gr

inikol@aueb.gr

References

• Bangerter, A., Roulin, N., & Konig, C. J. (2012). Personnel Selection as a Signaling Game. Journal of Applied Psychology, 97(4), 719-738.

• Chamorro-Premuzic, T., Winsborough, D., Sherman, R. A., & Hogan, R. (2016). New Talent Signals: Shiny New Objects or a Brave New World? Industrial and Organizational Psychology-Perspectives on Science and Practice, 9(3), 621-640.

• Gilliland, S. W., & Steiner, D. D. (2012). Applicant Reactions to Testing and Selection. In N. Schmitt (Ed.), The Oxford Handbook of Personnel Assessment and Selection (pp. 629-666). Oxrord: Oxford University Press.

• Hiemstra, A. M., & Derous, E. (2015). Video résumés portrayed: findings and challenges. In I. Nikolaou & J. K. Oostrom (Eds.), Employee Recruitment, Selection and Assessment. contemporary issues for theory and practise(pp. 45-60). London: Routledge/Psychology Press.

• Karim, M. N., Kaminsky, S. E., & Behrend, T. S. (2014). Cheating, reactions, and performance in remotely proctored testing: An exploratory experimental study. Journal of Business and Psychology, 29(4), 555-572.

• Kluemper, D. H., Rosen, P. A., & Mossholder, K. W. (2012). Social Networking Websites, Personality Ratings, and the Organizational Context: More Than Meets the Eye? Journal of Applied Social Psychology, 42(5), 1143-1172.

• Lievens, F., & Slaughter, J. E. (2016). Employer image and employer branding: What we know and what we need to know. Annual Review of Organizational Psychology and Organizational Behavior, 3, 407-440.

• McCarthy, J. M., Bauer, T. N., Truxillo, D. M., Anderson, N. R., Costa, A. C.,& Ahmed, S. M. (2017). Applicant Perspectives During Selection: A Review Addressing “So What? “What’s New?,” and “Where to Next?”.Journal of Management, 43(6), 1693-1725.

• Nikolaou, I. (2014). Social Networking Web Sites in Job Search and Employee Recruitment. International Journal of Selection and Assessment, 22(2), 179-189.

• Nikolaou, I., & Judge, T. A. (2007). Fairness reactions to personnel selection techniques in Greece: The role of core self-evaluations. International Journal of Selection and Assessment, 15(2), 206-219. 25

References

• Nikolaou, I. & Lagou, I. (in preparation). Applicant reactions and technology-oriented selection methods.

• Nikolaou, I., Bauer, T. N., & Truxillo, D. M. (2015). Applicant Reactions to Selection Methods: An Overview of Recent Research and Suggestions for the Future. In I. Nikolaou & J. K. Oostrom (Eds.), Employee Recruitment, Selection, and Assessment. Contemporary Issues for Theory and Practice (pp. 80-96). Hove, East Sussex: Routledge.

• Reynolds, D., & Dickter, D. (2017). Technology and employee selection. In J. L. Farr & N. T. Tippins (Eds.), Handbook of employee selection (pp. 855-873). New York: Routledge.

• Reynolds, D. H., & Dickter, D. N. (2010). Technology and employee selection. In J. L. Farr & N. T. Tippins(Eds.), Handbook of employee selection (pp. 171-194). New York: Taylor & Francis.

• Ryan, A. M., & Ployhart, R. E. (2014). A Century of Selection. Annual Review of Psychology, 65(1), 693-717. Tippins, N. T. (2015). Technology and Assessment in Selection. Annual Review of Organizational Psychology and Organizational Behavior, 2(1), 551-582. doi:10.1146/annurev-orgpsych-031413-091317

• Van Iddekinge, C. H., Lanivich, S. E., Roth, P. L., & Junco, E. (2016). Social media for selection? Validity and adverse impact potential of a Facebook-based assessment. Journal of Management, 42(7), 1811-1835.

• Petty, R.E., & Cacioppo, J.T. (1986). The Elaboration Likelihood Model of persuasion. New York: Academic Press.

• Roth, P. L., Bobko, P., Van Iddekinge, C. H., & Thatcher, J. B. (2013). Social Media in Employee-Selection-Related Decisions: A Research Agenda for Uncharted Territory. Journal of Management, 42(1), 269-298.

• Van Hoye, G. (2014). Word-of-mouth as a recruitment source: An integrative model. In K. Y. T. Yu & D. M. Cable (Eds.), The Oxford handbook of recruitment (pp. 251-268). New York: Oxford University Press.

• Van Hoye, G., & Lievens, F. (2007). Investigating Web‐Based Recruitment Sources: Employee testimonials vs word‐of‐mouse. International Journal of Selection and Assessment, 15(4), 372-382. 26