Over the last decades, psychological research has often highlighted that the theory of “rational” decision-making eventually prescribes choices from which humans systematically deviate. Remarkably, several Nobel laureates including Herbert Simon (1978), Daniel Kahneman (2002) and Richard Thaler (2017) have been prized for developing more realistic theories of human behavior and interaction.
In line with these theoretical developments, novel modelling methods have been proposed that allow more realistic descriptions of actual organizational behaviour. In particular, computational methods and statistical techniques allow nowadays to capture dynamics of latent psychological constructs and reproduce the emergence of novel organizational features. Ideally, these methods strive for recreating the complexity of macroscopic organizational structures without losing sight of individual human behavior.
The present call for special issue aims to collect a series of contributions (including original research articles, reports, or reviews) where such methods are employed in order to capture organizational dynamics. Potential methods to be applied to organizational studies include, but are not limited, to the following list:
Latent Class Growth Analysis
Hidden Markov chains
Nonlinear dynamical processes
Growth curve modeling
Recurrence quantification analysis