This paper describes a longitudinal business model (BM) evolution study for a sample of 63 original equipment manufacturers (OEMs) from the emerging additive manufacturing (AM) industry. This is done with the same sample of 63 OEMs for the year 2020. The evolutionary trajectory of each firm’s BM within the BM archetypes is observed and discussed relative to prior findings in the extant literature. A quantitative approach is used to glean which firms innovated their BMs the most, and which elements of the BM are most susceptible to innovation for each evolutionary trajectory.
Design/ methodology/ approach
The AMBM framework created by and is used for data collection. Secondary data is gathered from company websites to populate the framework using a binary input.
The k-means clustering algorithm using a Euclidian distance metric is used to group the data gathered into clusters, thereby creating the taxonomy. The data is processed comparatively, and a business model dynamic (BMD) score is computed for each firm.
Four BM archetypes were discovered. These are (1) Asset – focused Industrial Systems Vendors, (2) Comprehensive – service Industrial Systems Vendors, (3) Specialised Industrial Systems Vendors and (4) Home and Professional System Vendors.
The results indicate a trend of increased servitisation in the AM industry; all BM archetypes offer a significantly broader and more diverse spectrum of services. Increased servitisation also correlates with diversified revenue streams and partner networks, however further study is required to understand the causality of these correlations.
Also, it was observed that on average younger new entrants tend to target private consumers and professional prosumers with home and desktop printer types. While older incumbent firms are evolving to adopt industrial printers with enhanced product complexity, thereby targeting industrial business customers.
Substantial evidence was found based on the divergence of the AMBM taxonomy and the separate ambitions of older and younger firms that the AM industry is in a phase of technological ferment, one characterised by the new “maker-culture”.
This paper proposes a longitudinal business model evolution (BME) study of the AM industry. This type of study is unique to any other study of AMBMs.
Every industry is characterised by bespoke industrial forces. BM taxonomies are unlikely to be replicated for different emerging industries, therefore this taxonomy is only applicable to the AM industry.
This study hopes to provide a basis for future studies to understand the motivations behind (1) particular choices for business model innovation (BMI), (2) the processes of BMI firms deploy, as well as (3) the capabilities firms require for effective BMI and (4) the typical challenges firms face during BMI.