An integrated model proposal for impact analysis of risk components in supply chain management

Globalization, increasing competition, strengthening relationships among supply chain partners, and advancements in technology are among the various factors causing supply chains to become increasingly complex. This situation is associated with increasing uncertainties and emerging new risks that negatively affect companies. Therefore, identifying, assessing, and managing these risks is essential to establishing a profitable, competitive, and sustainable supply chain in the long term. Supply chain risk management (SRM) is a critical area of research and practice for managing these risks. The primary goal of this thesis is to create a model that aims to predict supply chain risks. In this context, it is primarily aimed to reveal the need for supply chain risk management and the advances in this field. In the study, trends in supply chain risk management (SCRM) were examined using a hybrid method that employs a holistic perspective along with fuzzy cognitive maps and Bayesian networks. When similar studies in the literature are examined, there are studies in which the Bayesian network approach is used for supply chain risk management modeling. Still, in this thesis study, an integrated model has been established to analyze the effect of risk components in supply chain management together with the document coding method. When similar studies in the literature are examined, it is observed that there are studies using the Bayesian networks approach for supply chain risk management modeling. However, in this thesis, the fuzzy cognitive maps method was initially used to analyze the impact of risk components in supply chain management along with the document coding method. Subsequently, the information obtained from the cognitive map was transformed, and a Bayesian Network focusing on conditional probability values was established and analyzed. A more suitable solution is aimed at the integrated model proposed within the scope of the study. The obtained results are thought to fill an important gap in the literature with their contribution to business applications.