Philip S. DeOrtentiis
Organizational Behavior and Human Resource Management · 2015–2018
A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Organizational Behavior and Human Resource Management — 40 citations into it
- Sociology and Political Science — 24 citations into it
- General Health Professions — 11 citations into it
Whom Philip S. DeOrtentiis trusts
Their strongest outbound trust, strongest first, inferred from their citations.
- F. Morgeson (in Organizational Behavior and Human Resource Management)
- Stephen E. Humphrey (in Organizational Behavior and Human Resource Management)
- Bennett J. Tepper (in Organizational Behavior and Human Resource Management)
Papers from Philip S. DeOrtentiis's perspective
Ordered by how strongly the researchers Philip S. DeOrtentiis trusts endorse each paper. Same corpus, a different order for every researcher.
- A Heuristic Method for Estimating the Relative Weight of Predictor Variables in Multiple Regression (Multivariate Behavioral Research)
- Using theory to evaluate personality and job-performance relations: a socioanalytic perspective. (Journal of Applied Psychology)
- The Work Design Questionnaire (WDQ): developing and validating a comprehensive measure for assessing job design and the nature of work. (Journal of Applied Psychology)
- Examination of relationships among trait-like individual differences, state-like individual differences, and learning performance. (Journal of Applied Psychology)
- The relative importance of task, citizenship, and counterproductive performance to global ratings of job performance: a policy-capturing approach. (Journal of Applied Psychology)
- Methodology for Dealing With Duplicate Study Effects in a Meta-Analysis
- The Modeling and Assessment of Work Performance
- The predictive validity of cognitive ability tests: A UK meta-analysis
- Anger in Organizations: Review and Integration
- Effect size and power in assessing moderating effects of categorical variables using multiple regression: a 30-year review. (Journal of Applied Psychology)