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Purpose

Additive manufacturing (AM) adoption remains limited not only by technical and firm-level barriers, but also by systemic AM adoption barriers that arise across organizational boundaries. This study investigates how inter-organizational management mechanisms can be systematically designed to overcome these barriers by shifting the focus from intra-firm measures to actor constellations embedded in the AM ecosystem.

Design/methodology/approach

The research employs a qualitative-exploratory design based on 19 expert interviews within the German AM ecosystem. The GABEK-WinRelan analysis reconstructs barrier constellations and their associative linkages; an ordonomic governance framework interprets these constellations as inter-organizational dilemma structures.

Findings

The study identifies four barrier constellations and governance responses: intellectual property right insecurity requires traceable data-handling commitments; quality ambivalence requires credible quality signaling through certified material systems; standardization fragmentation requires sector-specific collective alignment and skill shortages require intermediary-supported investment in qualification pathways.

Practical implications

The findings provide manufacturing managers with a diagnostic heuristic based on two questions: whether a systemic AM adoption barrier reflects a unilateral or collective coordination problem, and whether addressing it requires self-binding or an enabling commitment service. The study offers actionable management strategies to foster trust, interoperability, quality assurance and skill development within manufacturing networks embedded in the AM ecosystem.

Originality/value

This paper advances AM adoption research by conceptualizing persistent systemic AM adoption barriers as inter-organizational dilemma structures and by linking them to distinct governance logics. It thereby moves beyond technical or firm-centric explanations and provides an incentive-based vocabulary for explaining how credible commitments and coordinated investments can support AM adoption in manufacturing networks.

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