Additive manufacturing (AM), commonly known as 3D printing, has been attracting attention from practitioners as well as academicians with its continuous evolution from being used primarily for prototyping to now end-product production. Despite this technology's current and future potential, few studies indicate that AM has not been extensively used across all industries. This dissertation addresses knowledge gaps by providing theoretical and empirical support for adopting AM through three essays that study the role of AM in restructuring supply chains. Essay 1 provides systematic support for AM implementation by developing a typology derived from technology-specific potentials and challenges to adopting AM. This study uses an exploratory research approach to collect and analyze data from semi-structured interviews of practitioners with deep knowledge of AM and supply chains from diverse industries. In Essay 2, our results show that AM adoption positively influences supply chain responsiveness and, in turn, reshoring decisions. Essay 3 compares different supply chain configurations based on traditional and AM. We developed a hybrid simulation model combining discrete event simulation and agent-based simulation and compared the performance in terms of wait time and costs. Our results indicate that under certain conditions, the centralized configuration delivers spare parts faster than the distributed configuration, contrary to previous literature findings. However, a hybrid configuration (a combination of centralized and decentralized) provides a better response (reduced wait time) than the traditional, centralized, and decentralized configurations. Collectively, the three essays provide academicians and practitioners with a more comprehensive understanding of how AM creates value for supply chains.