An information system (IS) upgrade is an essential way to enhance the competitiveness of an organization. Specifically, the decision making processes surrounding IS upgrades is one of the most important parts of an organization's competitiveness in regard to business sustainability. Previous research studies on IS upgrade decisions have focused on implementing a more efficient decision-making system by determining when IS upgrades should be performed based on the cost factor, from the perspective of both users and experts. However, if the decision making of an IS upgrade is delayed or not performed accurately due to the limitations of a specific business environment, such as a job, position, or cost, an organization can lose its business competitiveness. In this context, the present study determines the main factors involved in decision making processes surrounding IS upgrades, and analyzes the interrelations among these factors in an organization with regard to users, managers, and experts. The interpretive structural modeling (ISM) method is used as an analytical tool to analyze the characteristics and interrelations of factors based on a real system model called the User-Centered Training System (UCTS). Based on the results, the present study provides a deeper insight into decision-making factors and directional models, and allows for a more efficient management of the decision-making problem of an IS upgrade caused by differences in the business environment between each layer (i.e., users, managers, and experts). Specifically, according to our results, users are more likely to think about the positive effects and benefits they could have on their work, rather than about organizational benefits. By contrast, managers reason that IS upgrades should have a positive impact on the overall organizational goals and benefits. Finally, experts think that an IS upgrade should benefit both the organization and users. Taken together, the results of the present study are meaningful in that they clearly show the interrelationships between the decision-making factors on each of the levels.

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