source 7.1

Introduction

• The rapid advancement of the digital economy has led to the emergence of new technological methodologies for personnel selection.

• Importance of establishing an evidence base for digital selection procedures (DSPs) given the gap between innovation and research.

Main Categories of Digital Selection Procedures

• Online Applications: Standardized online forms aiding in the screening process.

  • Advantages: Increased efficiency, objectivity, and reduction in selection costs.

  • Limitations: Limited peer-reviewed literature on validity; often only declarative data collected.

  • Impacts on Applicant Reactions: First impressions about organization; perceptions of fairness influenced by system design.

• Online Psychometric Testing: Tests administered through internet or mobile.

  • Concerns: Measurement equivalence and test security; different findings on cognitive ability tests between formats (online vs. paper).

  • Applicant Reactions: Mobile devices introduce variability and can negatively affect performance due to distractions.

• Digital Interviews: Use of video conferencing or on-demand recorded interviews.

  • Comparison with Traditional Interviews: Some applications perceived as less fair; however, ratings often higher for pre-recorded interviews.

  • AI in Interviews: Potential for bias and concerns about fairness as AI evaluates applicants based on varying indicators.

• Gamified Assessments: Incorporation of game elements into selection processes.

  • Uses: Stand-alone assessments or to enhance existing evaluations like SJTs.

  • Evidence Gap: Limited peer-reviewed literature on their effectiveness and validity.

• Social Media as Assessment Tool: Utilizing candidates' digital footprints.

  • Benefits: Can provide insight into candidates' personality traits and overall fit.

  • Concerns: Privacy issues; some studies show weak correlations between social media evaluations and job performance.

Critical Appraisal of the Evidence Base for DSPs

• Validity Issues: Need for criterion validity studies on DSPs as traditional methods may no longer apply.

• Adverse Impact: Limited research on subgroup differences; highlights risks of bias in algorithms used for DSP evaluations.

• Privacy Concerns: Increasing scrutiny regarding the ethical implications of using social networks for selection processes.

Research Agenda for Future Investigation

1. Understand construct validity of DSPs distinct from non-digital measures.

2. Establish guidelines for improving DSP validity based on user feedback.

3. Evaluate the criterion-related validities of DSPs, incorporating traditional comparisons.

4. Investigate adverse impact and bias within DSPs.

5. Develop updated perspectives on applicant reactions to DSPs.

6. Examine privacy concerns related to DSPs and their implications for organizations.

Conclusions

• Need for alignment between DSP implementation and rigorous research to inform best practices.

• Call to action for interdisciplinary collaboration to develop a comprehensive evidence base on DSP effectiveness and fairness.