Job Performance Ratings Research Articles

(De)Noise: Moderating the Inconsistency Between Human Decision-Makers

Prior research in psychology has found that people's decisions are often inconsistent. An individual's decisions vary across time, and decisions vary even more across people. Inconsistencies have been identified not only in subjective matters, like matters of taste, but also in settings one might expect to be more objective, such as sentencing, job performance evaluations, or real estate appraisals. In our study, we explore whether algorithmic decision aids can be used to moderate the degree of inconsistency in human decision-making in the context of real estate appraisal. In a large-scale human-subject experiment, we study how different forms of algorithmic assistance influence the way that people review and update their estimates of real estate prices. We find that both (i) asking respondents to review their estimates in a series of algorithmically chosen pairwise comparisons and (ii) providing respondents with traditional machine advice are effective strategies for influencing human responses. Compared to simply reviewing initial estimates one by one, the aforementioned strategies lead to (i) a higher propensity to update initial estimates, (ii) a higher accuracy of post-review estimates, and (iii) a higher degree of consistency between the post-review estimates of different respondents. While these effects are more pronounced with traditional machine advice, the approach of reviewing algorithmically chosen pairs can be implemented in a wider range of settings, since it does not require access to ground truth data.

Same as it ever was: A clarification on the sources of predictable variance in job performance ratings

Same as it ever was: A clarification on the sources of predictable variance in job performance ratings

Selection tests work better than we think they do, and have for years

AbstractWe can make better decisions when we have a better understanding of the different sources of variance that impact job performance ratings. A failure to do so cannot only lead to inaccurate conclusions when interpreting job performance ratings, but often misguided efforts aimed at improving our ability to explain and predict them. In this paper, we outline six recommendations relating to the interpretation of predictive validity coefficients and efforts aimed at predicting job performance ratings. The first three focus on the need to evaluate the effectiveness of selection instruments and systems based only on the variance they can possibly account for. When doing so, we find that it is not only possible to account for the majority of the variance in job performance ratings that most select systems can possibly predict, but that we’ve been able to account for this variance for years. Our last three recommendations focus on the need to incorporate components related to additional sources of variance in our predictive models. We conclude with a discussion of their implications for both research and practice.

Relationship between enforcement of labor social welfare laws and internal CSR, job satisfaction: a qualitative study at commercial banks in Vietnam

This study aimed to explore the relationship between three factors: enforcement of labor social welfare labor laws, internal corporate social responsibility (CSR) implementation, and job satisfaction as perceived by managers in the commercial banking sector. The research utilized a qualitative research method – in-depth interviews based on a semi-structured questionnaire with 20 experienced managers from 11 commercial banks in Vietnam, an emerging economy. Findings indicated a positive reciprocal relationship between enforcement of social welfare labor laws and internal CSR responsibilities of enterprises. Additionally, enforcing labor social welfare laws and internal CSR implementation positively impacted employee job satisfaction. The study also identified five aspects of internal CSR implementation towards employees: (1) timely and full payment of wages, bonuses, and benefits; (2) establishing a conducive work environment; (3) policies addressing human rights, health, and safety at work; (4) fair and democratic treatment, providing training and career advancement opportunities, and protecting employees through organizational activities; (5) having legal norms, procedures, mechanisms for recording, feedback, monitoring, and reasonable evaluation of job performance. These findings contribute to enriching both theoretical understanding and practical implications regarding the interplay of these three factors in commercial banks, encouraging managers to effectively implement social welfare laws and internal CSR implementation. AcknowledgmentThis collaborative research involves scholars from the University of Law - Hue University and Duy Tan University. The authors extend their gratitude to both institutions for their support and assistance in facilitating the publication of this research. In addition, the authors would like to thank the Editor-in Chief and a reviewer for their helpful comments that in our view have helped to improve the quality of the manuscript significantly. This study was conducted based on decision No. 4741/QD-ĐHDT dated October 18, 2023 of Duy Tan University, Vietnam.

The evaluation of job performance as a mechanism for meeting institutional goals. A case study in the Risaralda, regional SENA

such as satisfaction, motivation, autonomy, or abandonment. However, its role in meeting organizational goals constitutes a fundamental and insufficiently explored topic. The purpose of the study was to establish the importance of evaluating work performance in organizations of the Colombian state sector and its influence on the achievement of the objectives of the Sena, regional Risaralda. The study had a mixed design that was developed as a case study. A literature review was carried out, a questionnaire was applied, semi-structured interviews were carried out, and inferences were drawn from participant observation. The results point to a divided assessment of the EDL performance evaluation as a tool for meeting the institutional goals of the entity. In addition, the need to raise awareness on the subject, delve into the perception of the factors associated with the process, and introduce changes based on the data obtained was confirmed.

Talent Management in Industry 4.0: A Bibliometric Review of Required Skills and Competencies

This bibliometric study systematically analyzes the evolving field of talent management within the context of Industry 4.0, employing VOSviewer for mapping and visualizing key research themes, collaborations, and temporal trends from 2012 to 2024. The analysis revealed distinct thematic clusters focusing on the integration of digital transformation within traditional HR practices, emphasizing core competencies, firm capabilities, and the evaluation of job performance. Temporal trends indicate a shift from foundational topics to more complex issues such as leadership competencies and the strategic implications of digital technologies. Density visualizations highlighted areas with heavy research concentration and potential gaps, suggesting opportunities for future studies particularly in emerging and less explored themes. The co-authorship analysis provided insights into collaborative networks, indicating a mix of well-established research groups and emerging scholars. This study not only maps the current landscape but also guides future research directions in talent management amidst rapid technological advancements.

Strategi Efektif dalam Merancang dan Mengevaluasi Kinerja Pekerjaan di Era Manajemen Kontemporer

In the contemporary organizational management landscape, job performance design and evaluation has become a major factor influencing organizational effectiveness and employee well-being. The application of advanced technologies such as FP-Growth and K-Means algorithms allows businesses, especially online stores, to adjust sales strategies based on consumer purchasing patterns, increasing operational efficiency and strategy relevance. Additionally, the use of methodologies such as the Balanced Scorecard and Analytical Network Process (ANP) provides a holistic performance evaluation framework, covering both financial and non-financial aspects, helping organizations identify areas of improvement and strategic alignment. Fair reward strategies and transformational leadership roles are proven to increase employee motivation and performance, while recognition of individual differences allows for adjustments in management approaches to create an inclusive and productive work environment. This research adopted a mixed methods approach to evaluate the impact of job design on employee performance, focusing on teachers in the Kalmunai Zone. Through surveys, interviews, and regression analysis, this research aims to provide a comprehensive understanding of the relationship between job design and employee performance. By integrating technology, a holistic approach and human-centered leadership, organizations can achieve sustainable and superior performance amidst dynamic changes in today's business landscape

Departures from linearity as evidence of applicant distortion on personality tests

AbstractTwo field studies were conducted to examine how applicant faking impacts the normally linear construct relationships of personality tests using segmented regression and by partitioning samples to evaluate effects on validity across different ranges of test scores. Study 1 investigated validity decay across score ranges of applicants to a state police academy (N = 442). Personality test scores had nonlinear construct relations in the applicant sample, with scores from the top of the distribution being worse predictors of subsequent performance but more strongly related to social desirability scores; this pattern was not found for the partitioned scores of a cognitive test. Study 2 compared the relationship between personality test scores and job performance ratings of applicants (n = 97) to those of incumbents (n = 318) in a customer service job. Departures from linearity were observed in the applicant but not in the incumbent sample. Effects of applicant distortion on the validity of personality tests are especially concerning when validity decay increases toward the top of the distribution of test scores. Observing slope differences across ranges of applicant personality test scores can be an important tool in selection.

Utilizing machine learning to predict employee turnover in high-stress sectors

This study investigates the application of machine learning techniques to predict employee turnover in high-stress sectors. The primary objective is to enhance retention strategies by accurately identifying potential turnover risks. The research utilizes a comprehensive dataset comprising various factors, including employee demographics, job satisfaction, performance metrics, and stress levels. Multiple machine learning algorithms, such as logistic regression, decision trees, random forests, and neural networks, are employed to build predictive models. The methodology involves data preprocessing, feature selection, model training, and evaluation. Cross-validation and hyper parameter tuning are performed to ensure the robustness and accuracy of the models. The performance of each algorithm is assessed using metrics such as accuracy, precision, recall, and the area under the receiver operating characteristic curve (AUC-ROC). Key findings reveal that machine learning models can effectively predict employee turnover, with random forests and neural networks demonstrating superior performance. Significant predictors of turnover include job satisfaction, stress levels, and performance ratings. The study concludes that integrating machine learning models into human resource practices can provide valuable insights for preemptive interventions, ultimately reducing turnover rates in high-stress environments. Future research should explore the integration of real-time data and the potential of deep learning techniques to further enhance predictive accuracy. Additionally, the ethical implications of using predictive models in HR decisions warrant careful consideration to ensure fairness and transparency. Keywords: Machine Learning (ML), Employee Turnover, Predictive Analytics, Human Resources (HR), High-Stress Sectors, Decision Trees, Random Forests, Extreme Gradient Boosting (XGBoost), Personalized Retention Strategies, Business Intelligence (BI) Tools, Data Quality, Ethical Considerations, Data Privacy, Natural Language Processing (NLP), Deep Learning, Real-time Data Analysis, Employee Engagement, Work-Life Balance, Organizational Performance, Data-Driven Insights.

U.S. Law Enforcement Officers’ Stress, Job Satisfaction, Job Performance, and Resilience: A National Sample

The current study examined reports of perceived stress, job satisfaction, and job performance ratings in a longitudinal study of 684 officers participating in the Officer Safety and Wellness (OSAW) Initiative. Structural equation models were estimated to examine direct effects and, in subsequent analyses, the moderating effects of officer resilience and agency wellness programming on both the stress-job satisfaction association and the job satisfaction-job performance association. Surveys were administered annually, with job performance assessed both in terms of a self-rating and a self-report of supervisory rating at each officer’s last performance review. Officers’ stress (wave 1) was negatively associated with job satisfaction (wave 2), which in turn was positively associated with supervisory ratings of job performance (wave 3). These associations remained significant among officers reporting low to moderate baseline resilience but the association between job satisfaction and performance dissipated among officers with high resilience. Stress was negatively related to job satisfaction for officers who had easy access to agency-based wellness programs, whether they had concerns about stigma or used the programs, or not. The association between stress and job performance varied according to program access, use, and concerns about stigma associated with use. Administrators and policymakers striving to retain a high-performance police workforce may consider these results in recruiting as well as academy and in-service wellness training and program decisions.

Observing Interviewees’ Inner Self: How Authenticity Cues in Job Interviews Relate to Interview and Job Performance

AbstractJob interviews are among the most popular selection methods. Previous research suggests that interviewees who are perceived as being authentic are evaluated more favorably in job interviews. However, little is known about which behavioral cues elicit perceptions of authenticity in others and whether interviewees who exhibit such authenticity cues are more likely to perform better in the job interview and on their actual job. Drawing from person perception theories, the purpose of this study is to introduce the concept of authenticity cues to interview research and to examine the extent to which authenticity cues are related to (a) raters’ perceptions of interviewee authenticity, (b) interviewer ratings of interview performance, and (c) supervisor ratings of job performance. We used video recordings from 181 employed individuals participating in a mock interview to observe and rate interviewees’ authenticity cues. Results indicate that observers can distinguish between verbal and para/nonverbal authenticity cues and that both verbal and para/nonverbal cues influence the extent to which interviewees are perceived as authentic by independent raters. Moreover, we found that interviewees’ para/nonverbal authenticity cues were particularly relevant to predicting interview performance, whereas only verbal authenticity cues were related to job performance. In our analyses, we further considered the role of first impressions in the interview, interviewees’ verbal cognitive ability, and interviewees’ extraversion. Implications for theories of person perception, authenticity research, and interview practice are discussed.

The Impact of Workplace Set-up on the Job Performance of an Employee

The COVID-19 crisis forced many changes to occur within organizations, which were necessary to keep the continuance of the organization’s operations. A cross-sectional explanatory quantitative research design was utilized to investigate the impact of Workplace setup on the Job Performance of Employees, whose work is non-technical in nature with ages Eighteen (18) to Forty (40). t-Test for Independent Samples was used to measure if the Working On-site and Work-from-Home arrangements were significantly different from the result of Job Performance. Many studies show the effect of Workplace Arrangement has an effect on Job Performance, however, analysis of the results showed that there was no significant difference. Further studies must take into consideration the sample size and the Job Performance evaluations of the Immediate Superior or the management. Whether the Employees are performing well in their positions, in the set metrics of the organization.

Job Analysis of Korean Horticultural Therapists for Developing Specialized Training Using Developing a Curriculum Method

To align with global trends and the swift pace of technological advancements, it is imperative to consistently update the professional standards and curriculum for horticultural therapists to meet evolving professional demands. This study used the developing a curriculum (DACUM) method to analyze the tasks and duties of Korean horticultural therapists and subsequently tailor a specialized training program for them. First, 11 experts in the horticultural therapy field participated in workshops to develop a DACUM chart that included the definitions, tasks, knowledge, skills, and attitudes of horticultural therapists. A job performance evaluation survey for horticultural therapists was also developed through these workshops. The 300 participants of the online survey were members of the Korea Horticultural Therapy and Welfare Association. The survey consisted of a 5-point Likert scale of the current performance level and future requirement level for each qualification grade. Demographic information and responses to each question were computed using a frequency analysis and percentages, grade-specific task performance evaluations comprised a one-way batch analysis of variance, and statistical significance levels were set to P < 0.05. The horticulture professional curriculum was based on competencies derived from the job analysis and online conferences with 10 professionals who participated in the DACUM workshops. The job analysis results revealed six duties with a total of 32 tasks. The results of the job performance evaluation showed that there was a great demand for the development of their convergence capabilities. Accordingly, in response to these results, new interdisciplinary convergence fields such as horticultural therapy and science (information technology), horticultural therapy, and humanities education were introduced into the specialized training. The results of this study will be valuable for improving the skills and expertise of horticulture therapists to meet social needs.

An updated meta-analysis of the interrater reliability of supervisory performance ratings.

Given the centrality of the job performance construct to organizational researchers, it is critical to understand the reliability of the most common way it is operationalized in the literature. To this end, we conducted an updated meta-analysis on the interrater reliability of supervisory ratings of job performance (k = 132 independent samples) using a new meta-analytic procedure (i.e., the Morris estimator), which includes both within- and between-study variance in the calculation of study weights. An important benefit of this approach is that it prevents large-sample studies from dominating the results. In this investigation, we also examined different factors that may affect interrater reliability, including job complexity, managerial level, rating purpose, performance measure, and rater perspective. We found a higher interrater reliability estimate (r = .65) compared to previous meta-analyses on the topic, and our results converged with an important, but often neglected, finding from a previous meta-analysis by Conway and Huffcutt (1997), such that interrater reliability varies meaningfully by job type (r = .57 for managerial positions vs. r = .68 for nonmanagerial positions). Given this finding, we advise against the use of an overall grand mean of interrater reliability. Instead, we recommend using job-specific or local reliabilities for making corrections for attenuation. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The Influence of Job Achievement, Work Experience and Performance Evaluation on Employee Position Promotion in the Regional Energy and Mineral Resources Department of North Sulawesi Province

This research aims to determine the influence of work performance, work experience and performance evaluation on promotion of employee positions at the North Sulawesi Province Energy and Mineral Resources Service. The sampling method used was a saturated sampling technique with a sample size of 81 respondents. The data analysis technique used is Multiple Linear Regression. The results of this research show that simultaneously, work performance, work experience and performance evaluation have a significant effect on employee promotion at the Regional Energy and Mineral Resources Service of North Sulawesi Province. However, if viewed partially, only performance evaluation has a significant positive influence on employee promotions. Work performance has an insignificant positive effect on employee promotion. Meanwhile, work experience does not have a significant influence on the promotion of employee positions at the Regional Energy and Mineral Resources Service of North Sulawesi Province.

HUMAN RESOURCE MANAGEMENT IN THE DIGITAL ERA

Human resource management (HRM) is changing dramatically in the age of digitization, with advances in information technology, data analytics, and automation. This study investigates the changing role of HRM in using digital tools to improve recruiting, staff involvement, growth of talent, and job performance evaluation. The use of artificial intelligence (AI), machine learning (ML), and big data into HR processes is changing the way businesses manage their personnel, allowing for more effectiveness, customization, and strategic choice-making. This study investigates both the potential and problems that personnel managers confront while responding to digital advancements. This research paper aims to find out the importance of digital tools like artificial intelligence, machine learning, and data analytics in improving HR activities such as staffing, training, and worker assessment and the problems that HR professionals face while embracing and integrating new technology while maintaining human-centered management techniques. It was found that the change to digital HR involves careful consideration of data protection, ethical AI use, and the need to combine technology with the human touch in order to retain employee well-being and company culture.

Depression, anxiety, stress, and job performance among Turkish nurses in the early post-earthquake period.

Individual and social concerns can negatively affect nurses' mental health during a large-scale earthquake's early stages, making it challenging to perform their professional responsibilities. This cross-sectional correlational study aimed to examine the relationship between depression, anxiety, and stress levels Turkish nurses experienced during an earthquake's early period. The nurses participating in this study were not directly present in the earthquake-affected area. The study was conducted on 232 nurses between February 10 and 25, 2023. The data were collected using the Depression, Anxiety,Stress-21 Scale and the Job Performance Evaluation Form developed by the researchers through a literature review. These were used to investigate nurses' work motivation changes due to the earthquake. The study followed the STROBE checklist for cross-sectional studies. The participants' depression levels were severe, anxiety levels were extremely severe, and stress levels were moderate following the earthquake. Nurses who felt exhausted experienced reduced energy levels toward their work and reported a decrease in their desire, effort, and work motivation to perform well. In addition, they had higher depression, anxiety, and stress scores (p<0.005). Psychological difficulties, including depression, anxiety, and stress experienced by nurses not directly present in an earthquake-affected area, reduced their professional efforts and motivation and negatively affected the patient care process. Further studies should focus on conducting comparative studies in different cultures affected by natural disasters on the longitudinal analysis of the impacts of nurses' psychological distress on their job performance. Nursing policymakers should be aware of the negative psychological effects experienced by nurses during the early post-earthquake period, even if they are not directly present in the earthquake-affected area. The study recommended that nurses should be provided with psychological support to deal with the negative effects of natural disasters and maintain job performance, including the nursing care process.

Creativity During Threat to Organizational Survival: The Influence of Employee Creativity on Downsizing Survival Selection

Although research consistently shows that employee creativity contributes to positive outcomes for teams and organizations, we have limited insight into how employee creativity shapes the outcomes of those employees who demonstrate such creativity, particularly in the context of environmental uncertainties. Drawing from event system theory and threat rigidity theory, we argue that under a threat to organizational survival, incremental creativity has a positive, and radical creativity has a negative, indirect effect on downsizing survival selection via manager evaluations of employee job performance. Study 1 uses a unique three-wave, three-source field study ( n1 = 186) to provide support for our hypotheses. Studies 2 and 3 use experimental data ( n2 = 410, n3 = 565) involving different scenarios of threats to organizational survival (i.e., organization's innovation failure, competitor's successful innovation) that provide further support for the hypothesized effects of radical creativity on manager evaluations of employee job performance. Post-hoc analyses reveal novel insights into how managers’ creativity preferences can influence their evaluation of the job performance of employees who demonstrate incremental creativity during threatening events.

Finding better raters: The role of observer personality on the validity of observer-reported personality in predicting job performance

Drawing on Funder’s Realistic Accuracy Model, we investigate key sources of variance in the criterion-related validity of observer-reported personality in predicting target job performance. Specifically, this study builds theory on how observer personality impacts (a) access to and (b) processing of personality cues, influencing the extent to which observer-ratings of target personality predict supervisor ratings of target job performance. Results from a multisource field study (n = 301) indicate that observer-ratings of personality have the potential to capture both higher relative and incremental predictive validity over self-ratings. However, the extent to which observer-ratings outperform self-ratings depends upon personality characteristics of the observers, such that predictive validities are highest when observers score high on measures of conscientiousness, openness, and emotional stability.

Within-person personality variability in the work context: A blessing or a curse for job performance?

Only recently, the question whether within-person personality variability is a blessing or a curse for job performance has reached the agendas of industrial and organizational (I-O) psychology researchers. Yet, this limited stream of research resulted in inconsistent findings, and only little understanding exists about the role of rater source and mean-level personality in this relationship. Broadly following socioanalytic theory, the present study examined the extent to which self- and other-rated within-person personality variability predicts self- and other-rated job performance, and whether this is moderated by mean-level personality. Within-person personality variability indices and job performance evaluations were obtained from an experience sampling study including N = 166 teachers, N = 95 supervisors, and N = 69 classes (including 1,354 students). Results showed that-above and beyond the effects of mean-level personality-self-rated within-person variability was positively associated with self-rated job performance, while other-rated within-person variability was negatively associated with other-ratings of performance. Many interactions with mean-level personality were found, mainly demonstrating negative effects of variability for those with a less adaptive personality profile (cf. variability as a "curse"), while showing positive effects of variability for those with a more adaptive trait profile (cf. variability as a "blessing"). Importantly, however, additional analyses provided little evidence for associations across type of rater source. These findings contribute to the field of I-O psychology by highlighting that perceptions of within-person personality variability may impact performance evaluations beyond personality traits, although its desirability seems to depend on individuals' personality trait level. Implications and limitations are discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).