Additive manufacturing (AM) is among the most disruptive technologies of Industry 4.0 due to its unique capabilities. Yet, empirical studies rarely analyze how AM influences firm performance (FP) through supply chain practices (SCP), particularly from a mediating perspective, and capture both linear and non-linear correlations. This study aims to examine the impact of AM on SCP, which in turn influences the FP in manufacturing firms undergoing digital transformation.
The model, grounded in the practice-based view (PBV) and dynamic capabilities theory, was tested using survey data from 193 Indian manufacturing firms. Partial least squares structural equation modeling (PLS-SEM) assessed hypothesized relationships, and artificial neural networks (ANN) identified non-linear effects.
The results show that AM implementation positively influences FP, with SCP serving as a key mediator. ANN analysis highlights process improvement, supply chain coordination, AM processes and customer service management as the most important predictors. These are specifically relevant to industrial firms seeking enhanced performance through technological innovation and flexible operational methods.
The study offers actionable insights for manufacturing managers by emphasizing not only the “what” (adopting AM) but also the “how” (embedding AM into supply chain routines) to achieve competitiveness.
This study extends PBV and dynamic capabilities theory by demonstrating how AM adoption, when aligned with SCP, enhances FP. It provides a novel framework explaining how firms can translate AM into operational routines and coordination practices, advancing the literature on digital transformation in manufacturing.
