Machine Learning - Special issue on learning with probabilistic representations
Organizational Learning: Creating, Retaining, and Transferring Knowledge
Organizational Learning: Creating, Retaining, and Transferring Knowledge
Communications of the ACM
TAN Classifiers Based on Decomposable Distributions
Machine Learning
Fostering the determinants of knowledge transfer: a team-level analysis
Journal of Information Science
Linking Bayesian networks and PLS path modeling for causal analysis
Expert Systems with Applications: An International Journal
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Central points of this paper are placed on team creativity and Bayesian network approach as an assistant means. Above all, we seek to intensify our PLS model by using Bayesian network (BN) approach as an ancillary role. Beyond managers' control, we emphasize a voluntarily and informally emergent structure and introduce a social network perspective within team creativity. In this sense, we propose a new integrative team creativity model in which shared leadership, interpersonal trust and knowledge sharing are included and their subsequent influence on team creativity is analyzed. For the sake of empirical analysis, an e-learning course was administered in a private university, and 40 teams were organized for this study. 249 valid questionnaires were garnered, and initially analyzed by PLS (Partial least squares) model. Then, we suggested a new PLS model based on the results of Bayesian networks, and confirmed the successful application of our proposed approach.