Personnel Selection Practices Research Articles

The validity of general cognitive ability predicting job-specific performance is stable across different levels of job experience.

Decades of research in industrial-organizational psychology have established that measures of general cognitive ability (g) consistently and positively predict job-specific performance to a statistically and practically significant degree across jobs. But is the validity of g stable across different levels of job experience? The present study addresses this question using historical large-scale data across 31 diverse military occupations from the Joint-Service Job Performance Measurement/Enlistment Standards Project (N = 10,088). Across all jobs, results of our meta-analysis find near-zero interactions between Armed Forces Qualification Test score (a composite of math and verbal scores) and time in service when predicting job-specific performance. This finding supports the validity of g for predicting job-specific performance even with increasing job experience and provides no evidence for diminishing validity of g. We discuss the theoretical and practical implications of these findings, along with directions for personnel selection research and practice. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Longitudinal Effects of Employees’ Big Five Personality Traits on Internal Promotions Differentiated by Job Level in a Multinational Company

Promotions are central to individual career success. For organisations, it is crucial to identify and develop employees capable of higher-level responsibility. Previous research has shown that personality traits as inter-individual differences predict promotions. However, effects have mostly been examined on a broad factor level. This study investigated longitudinal effects of Big Five personality traits on both factor (neuroticism, extraversion, openness to experience, agreeableness, conscientiousness) and more detailed facet levels on promotions in employees of a multinational wholesale company (N = 1774, n = 343 promoted). We also explored how personality differentially impacts promotional likelihood as a matter of target job level (individual contributor vs. first- or senior-level manager roles). Overall, associations with promotions were detected for neuroticism (negative) and conscientiousness (positive). At the more nuanced facet level, all Big Five factors had at least one personality facet that was significantly related to promotions. Additionally, personality-promotion relationships were generally stronger for lower- rather than higher-level promotions. Taken together, our findings demonstrate that employee personality traits have a meaningful impact on who will be promoted and should hence be considered in organisational personnel selection, personnel development, and performance management practices.

Adverse impact reduction and job performance optimization via pareto-optimal weighting: A shrinkage formula and regularization technique using machine learning.

In personnel selection practice, one useful technique for reducing adverse impact and enhancing diversity is the Pareto-optimal weighting approach of De Corte et al. (2007). This approach produces a series of hiring solutions that characterize a diversity-job performance trade-off and can lead to more optimal selection outcomes (sometimes doubling the number of job offers for minority applicants without changing the job performance outcomes of personnel selection). Despite these advantages, recent research has identified a potential problem with the Pareto-weighting technique-Pareto solutions suffer from shrinkage upon cross-validation. To address the problem of shrinkage in the Pareto trade-off curve (i.e., diversity shrinkage and validity shrinkage), we offer two contributions. First, a shrinkage approximation formula is introduced (similar to a formula for adjusted R², but applicable to the entire Pareto trade-off curve). Second, we derive a novel technique for the regularization of Pareto-optimal predictor weights (borrowed from the field of machine learning), which is designed to produce predictor weights that are less vulnerable to shrinkage (similar to ridge regression and adapted from the elastic net technique). Both approaches-the proposed Pareto shrinkage formula and the proposed regularization technique-are then evaluated using Monte Carlo simulation. Recommendations are provided for approximating potential diversity-performance trade-off curves in personnel selection, while accounting for shrinkage. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Improving measurement and prediction in personnel selection through the application of machine learning

AbstractMachine learning (ML) is being widely adopted by organizations to assist in selecting personnel, commonly by scoring narrative information or by eliminating the inefficiencies of human scoring. This combined article presents six such efforts from operational selection systems in actual organizations. The findings show that ML can score narrative information collected from candidates either in writing or orally in response to assessment questions (called constructed response) as accurately and reliably as human judges, but much more efficiently, making such responses more feasible to include in personnel selection and often improving validity with little or no adverse impact. Moreover, algorithms can generalize across assessment questions, and algorithms can be created to predict multiple outcomes simultaneously (e.g., productivity and turnover). ML has even been demonstrated to make job analysis more efficient by determining knowledge and skill requirements based on job descriptions. Collectively, the studies in this article illustrate the likely major impact that ML will have on the practice and science of personnel selection from this point forward.

Personnel Selection in Australia: Identifying Research-Practice Gaps and Understanding the Importance of Culture Fit

This study examined current personnel selection practices in Australia including (a) the types of assessments used, (b) the factors considered when choosing assessments, and (c) the characteristics targeted in successful applicants. Participants from 68 organizations responded to a questionnaire that asked about current selection practices. Several areas where current practice deviated from research-supported best practice were identified. First, psychometric tests were used rarely: Cognitive ability tests were used by 26% of organizations and self-report questionnaires (e.g., personality inventories) by 18% of organizations. Second, when choosing assessments, the three most important considerations (in order) were the candidate experience, reducing bias, and that the assessment provides consistent scores; validity of the assessment was fourth. Finally, the most common characteristic organizations considered when selecting applicants was “culture fit.” Supplementary analyses to determine how culture fit was defined and assessed suggested there is little consistency in what it means and how it is measured.

Quasi-ipsative Forced-Choice Personality Inventories and the Control of Faking: The Biasing Effects of Transient Error

To date, experimental research on the effect of faking on personality measures has used two types of designs: within-subject designs and between-subjects designs. None of these designs permit us to control for the effects of transient error on faking. Using a Latin-square design (LSD), the current study examines the effects of faking on the Big Five as assessed by a quasi-ipsative forced-choice (FC) personality inventory. LSD is a type of experimental design that simultaneously permits us to control for between-subject differences, within-subject variability, and transient error. The sample consisted of 246 participants (four experimental groups, assessed twice, 2-3 week interval). The results showed that (1) faking effect size can be largely attributed to transient error and (2) the quasi-ipsative FC format shows great resistance to faking behavior. The average effect size (Cohen’s d) for the Big Five was 0.21, 0.12, and 0.09 for observed faking, transient error, and true faking, respectively. On average, 62% of observed faking effect size can be attributed to transient error. To conclude, we discuss the implications of these findings for the research and practice of personnel selection.

Little cause for concern: Analysis of gender effects in structured employment references

AbstractRecent research has highlighted the fact that narrative letters of recommendation in employment references could contribute to gender bias in personnel selection. Structured, quantitative employment references, however, may limit the opportunity for such biases to emerge. In a sample of nearly one million applicants and ratings by over four million employment reference providers, we found no meaningful effect of gender bias in highly structured, quantitative employment references across job levels and a wide variety of industries. Interestingly, and in contrast to existing theory, the effect of gender bias remained negligible across both stereotypically masculine and feminine jobs. Similarly, in a subsample of 5000 job applicants and 20,000 employment reference providers, coded verbatim comments of reference providers showed little practical gender differences in the frequency with which various comment types are made. These results suggest that highly structured, quantitative and semi‐structured, verbatim employment references are an effective tool in the advancement of fair and equitable personnel selection practices. Theoretical and practical implications are discussed, and future research is proposed.

Criterion Validity of Cognitive Reflection for Predicting Job Performance and Training Proficiency: A Meta-Analysis.

This article presents a meta-analysis of the validity of cognitive reflection (CR) for predicting job performance and training proficiency. It also examines the incremental validity of CR over cognitive intelligence (CI) for predicting these two occupational criteria. CR proved to be an excellent predictor of job performance and training proficiency, and the magnitude of the true validity was very similar across the two criteria. Results also showed that the type of CR is not a moderator of CR validity. We also found that CR showed incremental variance over CI for the explanation of job performance, although the magnitude of the contribution is small. However, CR shows practically no incremental validity over CI validity in the explanation of training proficiency. Finally, we discuss the implications of these findings for the research and practice of personnel selection.

Effects of Faking on the Predictive Validity of a Quasi-Ipsative Forced-Choice Personality Inventory: Implications for Sustainable Personnel Selection

Faking behavior is one of the main problems of personality measures. For this reason, determining the potential effects of faking on personality assessment procedures is relevant. The aim of this study has been to examine the impact of faking, induced in a laboratory setting, on the predictive validity of a quasi-ipsative forced-choice (FC) inventory based on the five-factor model. It also examined whether the magnitude of the predictive validity varied depending on the type of criteria analyzed (self-reported performance ratings and grade point average). The participants were 939 students from the University of Santiago de Compostela. As expected, the results showed that: (1) conscientiousness is the best predictor of performance even under faking response conditions; (2) conscientiousness predicts performance better when it is assessed using rating scales; and (3) reliability and validity were attenuated under faking conditions. Finally, we discuss the implications of these findings for the research and practice of personnel selection.

Embedded in context: How time and distance affect the convergence of personnel selection practices

AbstractThe debate on convergence versus divergence or stasis in human resource management (HRM) practices over time is still ongoing. We look at configurations of organisations' personnel selection practices and empirically analyse the role of geographic, cultural and regulatory institutional distance between countries for emerging similarity or dissimilarity in these practices. We also examine whether convergence occurred between 1995 and 2015. Based on the Cranet data of 25,869 organisations from 42 countries and statistical tests using energy distance, we find a pattern over time, moving from stasis to divergence. In addition, personnel selection configurations relate to cultural and regulatory institutional differences in the sense that smaller distances lead to higher similarity. This is not the case, however, for geographic distance. Our study adds to the debate on HRM convergence and offers a new method of analysis for other areas of HRM research where configurations instead of single HRM practices play a role.

Digital Transformation of HR Technologies

This article involves a study of the personnel management technologies digitalization degree based on the results of the SAP, Deloitte and Hays report, published in 2019. The analysis demonstrated HR automatization dependence on the size and specialization of organizations. The larger the company, the more complex personnel management processes are. The article defines four digitalization levels from the paper approach to the active use of artificial intelligence systems. Industries with the highest automatization percentage are identified. The article takes a closer look at personnel recruitment, selection, adaptation and training practices performed with the use of appropriate tools and programs. Among the most laborious recruitment functions stand communication with potential candidates, testing and interviewing, especially in cases of mass recruitment. Specialized programs that process CVs, build ratings, conduct video interviews and online testing to optimize recruiter’s work. The advantages of chatbots and messengers for adaptation digitalization are pointed out. Most executives have a positive attitude to the transition to new automated HR methods. The role of e-learning and software training is outlined, and the advantages of webinars, test constructors, and distance learning implementation are analyzed. It is noted that one third of Russian companies are actively automatizing employee training and development technologies. The article also highlights the most important personnel management processes that demand digital transformation in the first place. The automatization necessity of management accounting, effectiveness analysis of the current HR system, and benefits calculation is justified. Gamification advantages are outlined, as they are used in adaptation, training and personnel assessment processes. Senior management, HR executives and information services role in moving to a new level of personnel management is emphasized. VTB, VTB 24 and Sberbank spendings on automated HR systems are reasoned. Conclusions on the need to invest in digital transformation of HR processes are drawn.
 Keywords: personnel management, technologies, digitalization, process

Communicating Validity Information to Differentially Experienced Audiences: The Effects of Numeracy and Nontraditional Metrics

One of the biggest challenges facing organizational researchers is convincing practitioners to adopt evidence-based personnel selection practices such as the structured interview. In this study, we examined the effects of nontraditional validity metrics and numeracy by presenting validity information about the structured interview to audiences with differing amounts of interview experience (students, working adults, and hiring managers). The results indicated that nontraditional metrics were associated with higher understanding, more positive attitudes, and greater perceptions of the usefulness of the structured interview. These effects were constant across differing levels of numeracy. Additionally, the results revealed that nontraditional metrics result in more positive perceptions because they facilitate greater understanding. Nontraditional metrics were, however, less effective when audiences had interview experience. These results can be leveraged by practitioners and researchers who are interested in more effectively communicating validity information about the structured interview.

Professional Selection of Personnel as a Factor of Sustainable Development of the Mining Region

The subject of the study is the organization of professional selection of personnel as a factor of sustainable development of the mining region. Dynamic changes in the market economy have created a number of problems in the ideology and practice of personnel selection in the coal industry, caused by the low level of academic mobility of specialists. The purpose of this work is to analyze the problems of professional selection of personnel in the coal industry in order to determine the level of academic mobility and develop proposals for their solution. Used research methods: analysis, specification, description, generalization modeling. The study revealed some problems of professional selection of personnel for the coal industry considered a deterrent to the sustainable development of the coal industry. These problems include the following drawbacks: the low level of expertise of experts in General, in matters of professional diagnostics, and that is important in today’s dynamic conditions, diagnostics of academic mobility of a specialist in the coal industry. The scheme of professional selection of personnel present, which can be applied in order to solve some of the listed problems. In conclusion, the article substantiates the fact that it is necessary to review and correct the existing methodological tools, methodology for selecting and evaluating the professional suitability of personnel for the coal industry.

“Attitudes do matter”: generic competences in the selection of Business graduates

Purpose The purpose of this paper is to determine what competences are considered critical for team and human resources (HR) managers when selecting inexperienced Business graduates. Second, the authors aim to find out differences existing among businesses and organizations according to company size, and very particularly, the resources used with respect to the inexperienced graduate personnel selection practices. Design/methodology/approach To this end, the authors have performed an empirical study consisting of two qualitative data-gathering processes and a survey. First, the authors completed 12 in-depth interviews, followed by three world cafés with HR managers and consultants. Second, a survey was also conducted with 186 experienced Business graduates, team managers or middle-level staff. Findings The main results support the idea that generic competencies are the ones most appreciated in graduates. Attitudes are among the generic competencies considered most critical in inexperienced Business graduates. In particular, intra-personal, followed by inter-personal attitudes and values, were the most frequently cited and highly valued competencies. In contrast, most of the specific knowledge competences that are required for Business graduates are taken for granted. For its part, the authors found that excelling inexperienced graduates are those who show convincing proofs of holding attitudinal competences, signaled through some experience of international interchange programs, or pre-graduate internships in companies. Also, the authors found that HR managers and consultants show clear differences of preference for a set of competences or another depending on the size of the recruiting company. In particular, generic competences of knowledge, abilities, attitudes and values rate higher among small firms than larger ones. Originality/value Finally, the authors give recommendations for faculties and business schools headed to a more intensive development of generic competences, and the learning of skills on how to tailor curricula during studies and how to find jobs.

Is Personnel Selection Another Case of HRM Convergence? An Empirical Analysis

The debate on convergence versus divergence or stasis of human resource management (HRM) practices over time is still raging. Going beyond single personnel selection practices and focusing on their...

The Five-Factor model and job performance in low complexity jobs: A quantitative synthesis

This article presents the results of four primary studies that investigated the degree to which the Big Five personality dimensions predict job performance in occupations with a low level of job complexity. Job performance was assessed as overall job performance (OJP), task performance (TP), and contextual performance (CP). The results showed that conscientiousness and emotional stability proved to be predictors of the three performance measures. In addition, extroversion was a relevant predictor of OJP and TP, and agreeableness was a predictor of CP. Implications for the theory and practice of job performance and personnel selection are discussed.

Moderator effects of job complexity on the validity of forced-choice personality inventories for predicting job performance

Research has demonstrated that job complexity moderates the validity of general mental ability (GMA), the relationship between personality and job satisfaction, and the relationship between GMA and job satisfaction. However, no published research has investigated whether job complexity moderates the criterion validity of the Five-Factor Model (FFM) of personality for predicting job performance. This paper reports a meta-analytic examination of the moderator effects of job complexity on the criterion validity of the FFM of personality as assessed with forced-choice inventories. In accordance with the hypotheses, the results showed that job complexity moderates negatively the validity of conscientiousness and emotional stability and that it moderates positively the validity of openness. The implications for personnel selection research and practice are discussed.

Structured behavioral interview as a legal guarantee for ensuring equal employment opportunities for women: A meta-analysis

Equal employment opportunities for women are a legal requirement in many legal environments, including the United States (US) and European Union (EU) legislations. In this context, indirect discrimination in the access to jobs is an illegal practice. For this reason, personnel selection procedures must be fair for protected-by-law groups. Specifically, gender discrimination is the focus of research on employment interviews. This article presents a meta-analysis of gender differences in the scores in structured behavioral interviews (SBI). A database was created consisting of studies conducted with real candidates and employees. Psychometric meta-analysis methods were applied. The results showed that the SBI is fair for women and men and does not show evidence of adverse impact and indirect discrimination. Implications for the practice of personnel selection are discussed and future research is suggested.

Cross-Cultural Differences in the Attitude Toward Applicants’ Faking in Job Interviews

This study questions whether applicants with different cultural backgrounds are equally prone to fake in job interviews, and thus systematically examines cross-cultural differences regarding the attitude toward applicants’ faking (an important antecedent of faking and a gateway for cultural influences) on a large scale. Using an online survey, employees’ (N = 3252) attitudes toward faking were collected in 31 countries. Cultural data were obtained from the Global Leadership and Organizational Behavior Effectiveness project (GLOBE). Attitude toward faking can be differentiated into two correlated forms (severe/mild faking). On the country level, attitudes toward faking correlate in the expected manner with four of GLOBE’s nine cultural dimensions: uncertainty avoidance, power distance, in-group collectivism, and gender egalitarianism. Furthermore, humane orientation correlates positively with attitude toward severe faking. For international personnel selection research and practice, an awareness of whether and why there are cross-cultural differences in applicants’ faking behavior is of utmost importance. Our study urges practitioners to be conscious that applicants from different cultures may enter selection situations with different mindsets, and offers several practical implications for international personnel selection. Cross-cultural research has been expected to answer questions of whether applicants with different cultural backgrounds fake to the same extent during personnel selection. This study examines and explains cross-cultural differences in applicants’ faking in job interviews with a comprehensive sample and within a coherent theoretical framework.

Generating Race, Gender, and Other Subgroup Data in Personnel Selection Simulations: A pervasive issue with a simple solution

In the past 25 years, organizational researchers and practitioners have relied heavily on computer simulation research to understand how group mean differences and correlations affect overall validity and adverse impact in protected groups (e.g., racial/ethnic groups and gender) as they relate to personnel selection practices. We point out a multilevel issue affecting nearly all past simulations: The total correlations that these simulations intended to specify are somewhat distorted after group mean differences were introduced into the data. Although this distorting effect is minimal in most cases, it matters in some cases, and after all, the main virtue of statistical simulations is precision, both in the population parameters and sample data and statistics those parameters are supposed to generate. We demonstrate this distorting effect through one specific example, based on multiple predictors and meta‐analytic data, followed by a broader simulation for single predictors across a wide variety of selection conditions. Rather than merely point out this problem, we also provide a straightforward solution: multilevel formulas that incorporate both between‐ and within‐group correlations that always correct for this biasing problem, yielding more accurate simulation results. We conclude by discussing applications and promising extensions of this work.