Integrating Fuzzy Cognitive Mapping and Bayesian Network Learning for Supply Chain Causal Modeling

摘要

In this study, by integrating fuzzy cognitive mapping (FCM) and causal Bayesian network (CBN) learning, a model of causal links among supply chain enablers, supply chain management practices and supply chain performances is developed. For FCM development, fuzzy causal knowledge of a panel of experts in SCM is elicited. Also, an industry survey data used in a Bayesian learning process to create a CBN. By applying analytical modifications, the resultant CBN model is modified to reach better fit indices, suggesting a new approach in Bayesian learning. Integrating FCM and CBN models, resulted in more valid causal relations that are based on these two different methodologies. The findings of this study support the notion that SC enablers, especially IT technologies, don't have direct impact on SC performance. Also it is revealed that in any tier of supply chain concepts; there may be some important intra-relations which worth further studies.