During the last two decades, many companies have reshored their manufacturing operations to the home country, reversing previous offshoring decisions. Reshoring is a strategic decision for manufacturing companies because it is costly, complex, dynamic; thus, it is an important topic for research. Nevertheless, there is a research gap in how the reshoring decision-making process is modeled. Therefore, the overall purpose of this research is to increase the understanding of the reshoring decision-making process. The purpose is fulfilled through two research questions: (1) what is the state-of-the-art of reshoring decision-making process? and (2) how the reshoring decision-making process can be explored using a system dynamics model? The research design includes a literature review, modeling, and an expert interview. 

The findings indicate that the state-of-the-art of reshoring decision-making process comprises the drivers, barriers, and other factors are variables that motivate or hinder reshoring decision-making. However, their behavior varies over time and context. Environment and sustainability topics are not completely neglected in the decision-making process. Nevertheless, they are not a priority in reshoring decisions. The developed system dynamics model identifies relationships between the variables of reshoring decisions and how one variable can have a cause-and-effect relationship with another. During modeling of the reshoring decision-making, the complexity considerably increases as more variables are considered in the model. The developed system dynamics model provides a holistic view of the variables, their relationships, dynamics, and the overall complexity of the reshoring decision-making process. 

The research has implications for researchers because it increases the understanding of reshoring decision-making concerning the variables involved and relationships among them. Furthermore, this research contributes to the overall topic of reshoring by addressing modeling aspects. The research has implications for practitioners because it contributes to increasing the practitioners’ visualization of the decision-making, which can be used to communicate with various stakeholders. In order to advance this highly relevant field, it is recommended to quantify relationships among the variables that the developed system dynamic model can be simulated.