Background: The aim of this paper is to introduce weighted interpretive structural modeling approach to supply chain risk management efforts by presenting an application to identify micro risks of logistics service providers at the industry level in Turkey. Methods: In this research, eighteen risk factors in the logistics sector have been identified through both literature review and recommendations from a group of academicians and experts in the sector. A survey was conducted to rank these risks. They were further analyzed through a weighted interpretive structural modeling (WISM) approach in order to demonstrate mutual relationships among these risks. Results: Finally, using a WISM approach, an analysis was conducted to identify the driving and dependence power of the risk factors. This study covers a variety of micro-risk factors of logistics service providers and demonstrates the relationships among them and clusters them based on their driving and dependence power. Conclusions: Such a clustering of the risk factors helps us identify those that affect the others and are of paramount importance in risk management and mitigation.