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To remain viable in today's highly competitive business environments, it is crucial for organizations to attract and retain top candidates. Hence, interviewers have the goal not only of identifying promising applicants but also of representing their organization. Although it has been proposed that interviewers' deliberate signaling behaviors are a key factor for attracting applicants and thus for ensuring organizations' success, no conceptual model about impression management (IM) exists from the viewpoint of the interviewer as separate from the applicant. To develop such a conceptual model on how and why interviewers use IM, our qualitative study elaborates signaling theory in the interview context by identifying the broad range of impressions that interviewers intend to create on applicants, what kinds of signals interviewers deliberately use to create their intended impressions, and what outcomes they pursue. Following a grounded theory approach, multiple raters analyzed in-depth interviews with interviewers and applicants. We also observed actual employment interviews and analyzed memos and image brochures to generate a conceptual model of interviewer IM. Results showed that the spectrum of interviewers' IM intentions goes well beyond what has been proposed in past research. Furthermore, interviewers apply a broad range of IM behaviors, including verbal and nonverbal as well as paraverbal, artifactual, and administrative behaviors. An extensive taxonomy of interviewer IM intentions, behaviors, and intended outcomes is developed, interrelationships between these elements are presented, and avenues for future research are derived., ((c) 2016 APA, all rights reserved).)

This study contributes to the literature on why selection procedures that are based on the behavioral consistency logic (e.g., structured interviews and assessment centers) are valid predictors of job performance. We rely on interactionist theories to propose that individual differences in assessing situational demands explain true variance in performance in selection procedures and on the job. Results from 124 individuals in a simulated selection process showed that the assessment of situational demands was related to both selection and job performance. Individual differences in assessing situational demands also contributed to the criterion-related validity of assessment center and structured interview ratings, offering a complementary explanation as to why selection procedures based on the notion of behavioral consistency predict job performance.

Personnel selection involves exchanges of information between job market actors (applicants and organizations). These actors do not have an incentive to exchange accurate information about their ability and commitment to the employment relationship unless it is to their advantage. This state of affairs explains numerous phenomena in personnel selection (e.g., faking). Signaling theory describes a mechanism by which parties with partly conflicting interests (and thus an incentive for deception) can nevertheless exchange accurate information. We apply signaling theory to personnel selection, distinguishing between adaptive relationships between applicants and organizations, among applicants, and among organizations. In each case, repeated adaptations and counteradaptations between actors can lead to situations of equilibrium or escalation (arms races). We show that viewing personnel selection as a network of adaptive relationships among job market actors enables an understanding of both classic and underexplored micro- and macro-level selection phenomena and their dynamic interactions., ((PsycINFO Database Record (c) 2012 APA, all rights reserved).)

Although algorithm-based systems are increasingly used as a decision-support for managers, there is still a lack of research on the effects of algorithm use and more specifically on potential algorithmic bias on decision-makers. To investigate how potential social bias in a recommendation outcome influences trust, fairness perceptions, and moral judgement, we used a moral dilemma scenario. Participants (N = 215) imagined being human resource managers responsible for personnel selection and receiving decision-support from either human colleagues or an algorithm-based system. They received an applicant preselection that was either gender-balanced or predominantly male. Although participants perceived algorithm-based support as less biased, they also perceived it as generally less fair and had less trust in it. This could be related to the finding that participants perceived algorithm-based systems as more consistent but also as less likely to uphold moral standards. Moreover, participants tended to reject algorithm-based preselection more often than human-based and were more likely to use utilitarian judgements when accepting it, which may indicate different underlying moral judgement processes. [ABSTRACT FROM AUTHOR]

Research has examined trust in humans and trust in automated decision support. Although reflecting a likely realization of decision support in high‐risk tasks such as personnel selection, trust in hybrid human‐automation teams has thus far received limited attention. In two experiments (N1 = 170, N2 = 154) we compare trust, trustworthiness, and trusting behavior for different types of decision‐support (automated, human, hybrid) across two assessment contexts (personnel selection, bonus payments). We additionally examined a possible trust violation by presenting one group of participants a preselection that included predominantly male candidates, thus reflecting possible unfair bias. Whereas fully‐automated decisions were trusted less, results suggest that trust in hybrid decision support was similar to trust in human‐only support. Trust violations were not perceived differently based on the type of support. We discuss theoretical (e.g., trust in hybrid support) and practical implications (e.g., keeping humans in the loop to prevent negative reactions). Practitioner points: (a)What is currently known about the topic of our study: Automated decision‐support (DS) often fueled by artificial intelligence can be perceived more negatively in selection tasks than human DSThe task context can modulate trust in automated DSDepending on the agent (human or system), trust violations can be perceived differently (b)What our Paper adds to this: In both examined contexts (selection for bonus payments; personnel selection), system DS was trusted less compared to human DSFairness issues in a decision negatively impacted trust but did not lead to different reactions based on the type of agent that produced themHybrid DS is perceived on par with human DS and better than system DS when it comes to trust (c)The implications of our study findings for practitioners: Full automation of HR related tasks can be perceived negatively, even if the task may seem suited for automationAvoid fairness issues in selection as they negatively impact trust regardless of the agent that produced themAdding a human to an automated DS (i.e., realizing hybrid DS) can alleviate negative effects on trust associated with full automation. [ABSTRACT FROM AUTHOR]

Applicants seem to react negatively to artificial intelligence‐based automated systems in personnel selection. This study investigates the impact of different pieces of information to alleviate applicant reactions in an automated interview setting. In a 2 (no process information vs. process information) × 2 (no process justification vs. process justification) between‐subjects design, participants (N = 124) received respective information and watched a video showing an automated interview. Testing mediation effects via different applicant reaction variables indicated that process justification is better than process information which can even impair applicant reactions. However, information did not increase organizational attractiveness compared to not receiving any information. This study sheds light on what type of information contributes to positive and negative applicant reactions to automated systems. [ABSTRACT FROM AUTHOR]

Several faking theories have identified applicants' cognitive ability (CA) as a determinant of faking—the intentional distortion of answers by candidates—but the corresponding empirical findings in the area of personality tests are often ambiguous. Following the assumption that CA is important for faking, we expected applicants with high CA to show higher personality scores in selection situations, leading in this case to significant correlations between CA and personality scores, but not in nonselection situations. This meta‐analysis (66 studies, k = 115 individual samples, N = 46,265) showed this pattern of results as well as moderation effects for the study design (laboratory vs. field), the response format of the personality test, and the type of CA test. [ABSTRACT FROM AUTHOR]

Although research demonstrates that self‐verification striving can have positive outcomes in the hiring process, it remains unclear how this drive to present oneself authentically manifests in candidates' behavior during job interviews. We examine whether self‐verifying behavior, including revelation of negative information about the self, is related to success in job interviews. Study 1 showed that self‐verification striving among 112 MBA students predicted their self‐verifying behavior during mock job interviews, which in turn led to success in converting interviews into actual offers 6 months later. Using a sample of 102 recent job seekers, Study 2 showed that self‐verification striving was associated with the extent to which candidates disclosed negative information about themselves during real job interviews, ultimately predicting their interview success. [ABSTRACT FROM AUTHOR]

Recent research has highlighted competitive worldviews as a key predictor of faking—the intentional distortion of answers by candidates in the selection context. According to theoretical assumptions, applicants' abilities, and especially their cognitive abilities, should influence whether faking motivation, triggered by competitive worldviews, can be turned into successful faking behavior. Therefore, we examined the influence of competitive worldviews on faking in personality tests and investigated a possible moderation of this relationship by cognitive abilities in three independent high school and university student samples (N1 = 133, N2 = 137, N3 = 268). Our data showed neither an influence of the two variables nor of their interaction on faking behavior. We discuss possible reasons for these findings and give suggestions for further research. [ABSTRACT FROM AUTHOR]

Technologically advanced selection procedures are entering the market at exponential rates. The current study tested two previously held assumptions: (a) providing applicants with procedural information (i.e., making the procedure more transparent and justifying the use of this procedure) on novel technologies for personnel selection would positively impact applicant reactions, and (b) technologically advanced procedures might differentially affect applicants with different levels of computer experience. In a 2 (computer science students, other students) × 2 (low information, high information) design, 120 participants watched a video showing a technologically advanced selection procedure (i.e., an interview with a virtual character responding and adapting to applicants’ nonverbal behavior). Results showed that computer experience did not affect applicant reactions. Information had a positive indirect effect on overall organizational attractiveness via open treatment and information known. This positive indirect effect was counterbalanced by a direct negative effect of information on overall organizational attractiveness. This study suggests that computer experience does not affect applicant reactions to novel technologies for personnel selection, and that organizations should be cautious about providing applicants with information when using technologically advanced procedures as information can be a double-edged sword. [ABSTRACT FROM AUTHOR]