New research in the Journal of Business and Psychology highlights the benefits of applying synthetic data modeling to 360 assessment data.
Synthetic data models can learn the distinct features of a given dataset and then produce nearly identical imitations. Importantly, because these data are artificial, they preserve the anonymity and confidentiality of the respondents.
While providing two demonstrations of synthetic data models and a framework for applying these models, the authors point towards several opportunities for future applications, including, for example:
- Facilitating better open science practices through the sharing of sensitive data,
- Better examining understudied populations of leaders by synthesizing data to achieve sufficient sample sizes,
- Improving the representation of studies in literature reviews and meta-analyses.
By applying methodologies developed by data scientists to questions commonly facing leadership scholars, this paper highlights the power of leveraging multiple disciplines in the pursuit of new insights.
