A Bayesian Network-Based Management of Individual Creativity: Emphasis on Sensitivity Analysis with TAN

Creativity emerges as one of important resources for management. However, definitions of creativity have varied with researchers, and there is no universally agreed consensus about how to manage creativity in organizations. In this sense, managers who are interested in adopting specific type of creativity management strategy were confused. To avoid this problem, this study proposes a new method to creativity management by using a Bayesian Network (BN) that consists of nodes and arcs, and enables sensitivity analyses with various scenarios of interest. By focusing on individual creativity and its relationships with knowledge characteristic, intrinsic motivation, knowledge heterogeneity among team members, and organizational learning, we collected 222 valid questionnaires and performed what-if/goal seeking simulations based on TAN (Tree Augmented Naive Bayesian Network) structure. Empirical results were promising and its practical meanings were well interpreted.