Many new ventures position themselves along the additive manufacturing (AM) value chain to benefit from the quickly maturing technology. Yet, their business models and sources of value creation are largely unidentified. We compile a unique dataset with 160 entrepreneurial AM-firms using a leading crowd-sourced database and organize the data in a card file system. We code the data along multiple dimensions and apply a Latent Class Analysis to identify unique segments of firms that focus on different complementary activities along the AM value chain. By using the NICE framework, we additionally reveal the value creation mechanisms of each identified class. We identify four unique segments of AM-firms that focus on different complementary activities: (i) hardware providers, (ii) software and data experts, (iii) full-service providers, and (iv) manufacturing orchestrators. While a lot of value creation across these segments is currently still driven by novelty and innovation, AM-firms also introduce lock-in and complementary products and services to capture value beyond production. In characterizing value chain structures, we outline how firms can position themselves in this emerging industry.

Spare parts are a particularly interesting application for switching production from traditional manufacturing (TM) to additive manufacturing (AM). Research assessing AM has primarily addressed cost models centering on the production process or the operations management of separate spare parts. By combining case study, modeling, and design science elements, we adopt a holistic perspective and develop a design to examine the systematic leverage of AM in spare parts operations. Contextually grounded in problems faced by a leading material handling equipment manufacturer that is challenged by common characteristics of after-sales operations, we engage with practice to propose a portfolio level analysis examining the switchover share from TM to AM. Using a data set of 53,457 spare parts over 9 years, we find that up to 8% of stock keeping units (SKUs) and 2% of total units supplied could be produced using AM, even if unit production costs are four times those of TM. This result is driven by low demand, high fixed costs, and minimum order quantities in TM. Finally, we present the evaluation by the case company's management and highlight five areas of opportunity and challenge.