Predictors and consequences of faking in high-fidelity selection situations: Establishing a dual process model of faking

• Applicant: Professorin Ute-Christine Klehe, Ph.D.
• Subject Area: Social Psychology, Industrial and Organisational Psychology
• Term: from 2017 to 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 388241229

Studies show that up to 60% of candidates fake during personnel selection procedures. This makes faking a point of discussion and a concern for the accuracy of selection decisions. More specifically, research has shown that fakers can raise their performance evaluations in questionnaire measures (e.g. personality inventory) and partly in interviews, resulting in higher chances of being selected.Yet, research on faking shows a heavy imbalance. Much research has addressed faking in questionnaires and interviews, but very little is known as to whether faking also occurs in high-fidelity simulations such as AC exercises and how it influences candidates` performance in these procedures. Hence, the proposed research aims to find answers to the following questions: Does faking happen in high-fidelity exercises?; Can we predict faking in high-fidelity exercises? and How does faking influence candidates` performance in high-fidelity exercises?DO CANDIDATES FAKE IN HIGH-FIDELITY EXERCISES?The dominant line of argument is that high-fidelity exercises are resistant to faking due to the high cognitive resources already needed to master the exercise itself. Yet, different research results suggest that also high-fidelity exercises might be open to candidates actively shaping the impressions they make on observers. Yet, it has never been investigated whether faking occurs during high-fidelity exercises. Supporting results could trigger new research as well as advise practitioners on suitable measures in order to reduce candidates` faking tendencies during high-fidelity exercises. CAN WE PREDICT FAKING?Existing models on faking often use the theory of planned behavior in order to forecast candidates` faking during personnel selection. By answering this question, we target to test whether these models can be generalized to high-fidelity exercises or whether they need certain adjustments to be also applicable to predict faking in high-fidelity exercises. HOW DOES FAKING INFLUENCE CANDIDATES` PERFORMANCE IN HIGH-FIDELITY EXERCISES?Candidates` faking in questionnaires can increase their performance. In interactive selection procedures (e.g., interviews), this positive relationship is not as clear - some studies found positive effects while others found none or even negative effects on candidates' performance evaluations. Yet, faking research has not yet acknowledged that faking might potentially also have negative effects on candidates` performance, which might be able to explain the mixed results. Thus, we aim to answer this question by testing a model that includes positive as well as negative consequences of faking onto candidates` performance, the latter via a proposed effect of faking on candidates` sense of inauthenticity. Thus, our model also tries to explain how the different effects of faking come about.

• DFG Programme: Research Grants
• International Connection: Switzerland
• Cooperation Partner: Professor Dr. Martin Kleinmann