Advanced technologies such as additive manufacturing (AM) play a critical role in transforming the healthcare sector by enabling sustainable and resilient solutions that improve patient services and operational efficiency. Yet, the adoption of AM in the healthcare sector is limited. Understanding the knowledge drivers behind its adoption is crucial for its successful implementation and better healthcare performance. This study aims to explore how effective knowledge processes impact innovation, resilience, sustainability and enhanced service quality in healthcare organisations.
Drawing on the dynamic capabilities theory, the motivating factors for AM adoption are identified from the literature and verified with industry experts using the fuzzy Delphi method. Then the factors are ranked and categorised into cause-and-effect using different multicriteria decision-making methods. Subsequently, the rationale for the cause-and-effect linkages has been explained using a qualitative approach.
This study presents a knowledge-driven decision-support framework that demonstrates how AM facilitates environmental sustainability, operational resilience and performance improvement. Healthcare organisations can leverage this knowledge-structured guidance to make informed decisions aligned with regulatory sustainability mandates.
Existing studies examine AM in healthcare through separate lenses (e.g. resilience, sustainability and performance) without explaining how organisations can integrate these objectives in practice. This study addresses that gap by developing a knowledge-driven decision-support framework that links knowledge processes and dynamic capabilities to AM adoption pathways, thereby offering actionable and innovative strategies for healthcare organisations.
