Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-28T03:34:29.186Z Has data issue: false hasContentIssue false
  • English
  • Français

Do We Really Need New Constructs? An Argument for Adapting Individual Predictors to Dynamic Environments

Published online by Cambridge University Press:  28 July 2015

Lebena Varghese ,
Meghan I. H. Lindeman  and
Alecia M. Santuzzi
Lebena Varghese*
Affiliation:
Northern Illinois University
Meghan I. H. Lindeman
Affiliation:
Northern Illinois University
Alecia M. Santuzzi
Affiliation:
Northern Illinois University
*
Correspondence concerning this article should be addressed to Lebena Varghese, Department of Psychology, Northern Illinois University, Dekalb, IL 60115. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Extract

Neubert, Mainert, Kretzschmar, and Greiff (2015) argue that the variable and dynamic nature of new job roles requires employees to demonstrate skills such as complex problem solving (CPS) or collaborative problem solving (ColPS). We argue that assessing CPS and ColPS in place of traditional assessment would be criterion deficient. We argue that traditional personnel assessments are important even for 21st century jobs. In this commentary we attempt to (a) highlight the contribution of currently assessed individual predictors and job skills in relation to personnel selection and (b) discuss how those traditional assessments can inform performance even in dynamic environments, such as those experienced in team-based work.

Type
Commentaries
Information
Industrial and Organizational Psychology , Volume 8 , Issue 2 , June 2015 , pp. 294 - 301
Copyright
Copyright © Society for Industrial and Organizational Psychology 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bell, S. (2007). Deep-level composition variables as predictors of team performance: A meta-analysis. Journal of Applied Psychology, 92, 595–615. doi:10.1037/0021-9010.92.3.595CrossRefGoogle ScholarPubMed
Choi, H., & Levine, J. (2004). Minority influence in work teams: The impact of newcomers. Journal of Experimental Social Psychology, 40 (2), 273–280. doi:10.1016/s0022-1031(03)00101-xCrossRefGoogle Scholar
Driskell, J., Goodwin, G., Salas, E., & O'Shea, P. (2006). What makes a good team player? Personality and team effectiveness. Group Dynamics: Theory, Research, and Practice, 10, 249–271. doi:10.1037/1089-2699.10.4.249Google Scholar
Guion, R., & Highhouse, S. (2006). Assessing via tests. In Essentials of personnel assessment and selection (pp. 235–257). Mahwah, NJ: Erlbaum.Google Scholar
Hogg, M., & Hains, S. (1998). Friendship and group identification: A new look at the role of cohesiveness in groupthink. European Journal of Social Psychology, 28, 323–341.3.0.CO;2-Y>CrossRefGoogle Scholar
Hunter, J. (1986). Cognitive ability, cognitive aptitudes, job knowledge, and job performance. Journal of Vocational Behavior, 29 (3), 340–362. doi:10.1016/0001-8791(86)90013-8Google Scholar
Jackson, J., & Williams, K. (1985). Social loafing on difficult tasks: Working collectively can improve performance. Journal of Personality and Social Psychology, 49 (4), 937–942. doi:10.1037//0022-3514.49.4.937CrossRefGoogle Scholar
LePine, J. (2003). Team adaptation and postchange performance: Effects of team composition in terms of members’ cognitive ability and personality. Journal of Applied Psychology, 88, 27–39. doi:10.1037/0021-9010.88.1.Google Scholar
LePine, J. A., Colquitt, J. A., & Erez, A. (2000). Adaptability to changing task contexts: Effects of general cognitive ability, conscientiousness, and openness to experience. Personnel Psychology, 53, 563–593. doi:10.1111/j.1744-6570.2000.tb00214.xCrossRefGoogle Scholar
Lievens, F., Harris, M., Van Keer, E., & Bisqueret, C. (2003). Predicting cross-cultural training performance: The validity of personality, cognitive ability, and dimensions measured by an assessment center and a behavior description interview. Journal of Applied Psychology, 88, 476–489. doi:10.1037/0021-9010.88.3.476CrossRefGoogle Scholar
Motowildo, S., Borman, W., & Schmit, M. (1997). A theory of individual differences in task and contextual performance. Human Performance, 10, 71–83. doi:10.1207/s15327043hup1002_1CrossRefGoogle Scholar
Mullen, B., Johnson, C., & Salas, E. (1991). Productivity loss in brainstorming groups: A meta-analytic integration. Basic and Applied Social Psychology, 12, 3–23. doi:10.1207/s15324834basp1201_1CrossRefGoogle Scholar
Neubert, J., Mainert, J., Kretzschmar, A., & Greiff, S. (2015). The assessment of 21st century skills in industrial and organizational psychology: Complex and collaborative problem solving. Industrial and Organizational Psychology: Perspectives on Science and Practice.Google Scholar
Pauhus, P., Dzindolet, M., Poletes, G., & Camacho, L. (1993). Perception of performance in group brainstorming: The illusion of group productivity. Personality and Social Psychology Bulletin, 19, 78–89. doi:10.1177/0146167293191009Google Scholar
Tett, R., & Burnett, D. (2003). A personality trait-based interactionist model of job performance. Journal of Applied Psychology, 88, 500–517. doi:10.1037/0021-9010.88.3.500CrossRefGoogle ScholarPubMed