Decoding the Barriers to Additive Manufacturing Adoption in MRO Spare Parts Supply Chains: A TOE–RBV Perspective

Additive manufacturing technology (AMT) has the potential to transform spare parts supply chains by enabling on-demand production, digital inventory, and decentralized manufacturing. However, its adoption in maintenance, repair, and overhaul (MRO) environments remains constrained by multiple interrelated barriers. This study aims to identify the critical barriers to AMT adoption in MRO spare parts supply chains and examine their structural interdependencies and relative influence. To achieve this objective, an integrated methodological framework combining Grey Influence Analysis (GINA), Interpretive Structural Modeling (ISM), and MICMAC analysis is employed. GINA is used to assess the relative influence of the barriers, while ISM and MICMAC are used to establish their hierarchical relationships and driving-dependence characteristics. The findings reveal that capability-related barriers—including lack of technical expertise, inadequate training and awareness, lack of structural competency, and insufficient managerial support—emerge as the most influential driving factors affecting AMT adoption. These foundational barriers significantly influence intermediate technological constraints, which subsequently influence higher-level operational and strategic challenges including complex licensing policies and perceived lack of economic viability. The findings are interpreted through the technology–organization–environment (TOE) framework and resource-based view (RBV), highlighting the importance of organizational capabilities in shaping the ability of MRO organizations to respond to technological and environmental adoption conditions. The study contributes by extending AMT adoption research from barrier identification toward a theoretically grounded explanation of their hierarchical interdependencies and relative influence. Practically, the findings suggest that organizations should prioritize capability development, workforce training, management support, and technological and ecosystem readiness before pursuing broader AMT implementation.