TY - JOUR
T1 - Additive manufacturing in the medical sector : from an empirical investigation of challenges and opportunities toward the design of an ecosystem model
AU - Peron, Mirco
AU - Saporiti, Nicolò
AU - Shoeibi, Majid
AU - Holmström, Jan
AU - Salmi, Mika
N1 - Publisher Copyright:
© 2024, Emerald Publishing Limited.
PY - 2024/6/3
Y1 - 2024/6/3
N2 - Purpose: This works provides a thorough understanding of the challenges and opportunities associated with Additive Manufacturing (AM) adoption in the medical sector. Through this analysis, we aim to better understand when to adopt AM, how to do so, and how such adoption might change in the future. Design/methodology/approach: This research first conducted a systematic literature review (SLR) to identify AM challenges and opportunities in the medical sector, which were then validated through a Delphi study. The 18 Delphi study participants were also asked to suggest countermeasures for the challenges and help identify future AM adoption scenarios. Finally, these findings were analyzed according to the ecosystem pie model to design an ecosystem model for AM in the medical sector. Findings: Among the 13 challenges and 13 opportunities identified, the lack of a skilled workforce and the responsiveness achievable via AM were by far the most relevant challenge and opportunity. Moreover, the participants identified countermeasures for 10 challenges, as well as three future AM adoption scenarios. Finally, leveraging these findings, an ecosystem model was developed. Originality/value: This work contributes to the limited understanding of the AM challenges and opportunities in the medical sector. It helps medical practitioners to better understand the challenges and opportunities associated with AM and AM manufacturers to better identify where to focus their R&D efforts and how this would impact future AM adoption levels. Furthermore, this work extends current theory supporting the design of an ecosystem model for AM in the medical sector following the ecosystem pie model.
AB - Purpose: This works provides a thorough understanding of the challenges and opportunities associated with Additive Manufacturing (AM) adoption in the medical sector. Through this analysis, we aim to better understand when to adopt AM, how to do so, and how such adoption might change in the future. Design/methodology/approach: This research first conducted a systematic literature review (SLR) to identify AM challenges and opportunities in the medical sector, which were then validated through a Delphi study. The 18 Delphi study participants were also asked to suggest countermeasures for the challenges and help identify future AM adoption scenarios. Finally, these findings were analyzed according to the ecosystem pie model to design an ecosystem model for AM in the medical sector. Findings: Among the 13 challenges and 13 opportunities identified, the lack of a skilled workforce and the responsiveness achievable via AM were by far the most relevant challenge and opportunity. Moreover, the participants identified countermeasures for 10 challenges, as well as three future AM adoption scenarios. Finally, leveraging these findings, an ecosystem model was developed. Originality/value: This work contributes to the limited understanding of the AM challenges and opportunities in the medical sector. It helps medical practitioners to better understand the challenges and opportunities associated with AM and AM manufacturers to better identify where to focus their R&D efforts and how this would impact future AM adoption levels. Furthermore, this work extends current theory supporting the design of an ecosystem model for AM in the medical sector following the ecosystem pie model.
KW - Additive manufacturing (AM)
KW - Challenges
KW - Delphi study
KW - Ecosystem model
KW - Medical sector
KW - Opportunities
KW - Systematic literature review (SLR)
UR - http://www.scopus.com/inward/record.url?scp=85194842841&partnerID=8YFLogxK
U2 - 10.1108/IJOPM-12-2023-0948
DO - 10.1108/IJOPM-12-2023-0948
M3 - Article
AN - SCOPUS:85194842841
SN - 0144-3577
JO - International Journal of Operations and Production Management
JF - International Journal of Operations and Production Management
ER -