Abstract

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.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call