Recent effort in organizational psychology and organizational behavior (OPOB) research has placed increasing emphasis on understanding dynamic phenomena and processes. This calls for more and better use of dynamic modeling in OPOB research than before. The goals of this review are to provide an overview of the general forms of dynamic modeling in OPOB research, discuss three longitudinal data analytic techniques for conducting dynamic modeling with empirical data [i.e., time-series-based modeling, latent-change-scores-based modeling, and functional data analysis (FDA)], and introduce various dynamic modeling approaches for building theories about dynamic phenomena and processes (i.e., agent-based modeling, system dynamics modeling, and hybrid modeling). This review also highlights several OPOB research areas to which dynamic modeling has been applied and discusses future research directions for better utilizing dynamic modeling in those areas.
|Original language||English (US)|
|Number of pages||26|
|Journal||Annual Review of Organizational Psychology and Organizational Behavior|
|State||Published - Jan 1 2016|
- computational modeling
- dynamic modeling
- longitudinal data analysis