Your browser doesn't support javascript.
Building supply chain resilience and efficiency through additive manufacturing: An ambidextrous perspective on the dynamic capability view
International Journal of Production Economics ; : 108516, 2022.
Article in English | ScienceDirect | ID: covidwho-1814548
ABSTRACT
Following the COVID-19 outbreak, a wide range of scholars and practitioners have come to recognize the potential of Additive Manufacturing (AM) technology in building supply chain resilience and efficiency. However, it remains unclear how AM technology might be able to simultaneously build supply chain efficiency and resilience, given the often conflicting nature of these qualities. This paper employs an ambidextrous perspective on dynamic capability theory to investigate the potential of AM technology to solve this resilience-efficiency dilemma at the supply chain level. The research design involves a hybrid approach, combining focus groups and multiple case studies, with particular attention paid to the African supply chain context. The findings indicate that AM technology presents the potential to develop ambidextrous dynamic capabilities, leading to the reconciliation of resilience and efficiency at the supply chain level. Some determinants, such as data-driven systems, supply chain collaboration, innovation agility and knowledge are found to be critical to enable the development of those capabilities around AM-enabled manufacturing systems. The study contributes to the preparation of the global supply chain for the post-COVID era, where digital technologies such as AM will be fundamental for both building resilience and efficiency simultaneously. Practitioners in emerging economies may benefit directly from the outcomes of this study. Furthermore, managers and policy-makers in developed countries may be made aware of the significance of using AM technology in emerging countries to enhance the performance of the global supply chain.
Keywords

Full text: Available Collection: Databases of international organizations Database: ScienceDirect Language: English Journal: International Journal of Production Economics Year: 2022 Document Type: Article

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: Databases of international organizations Database: ScienceDirect Language: English Journal: International Journal of Production Economics Year: 2022 Document Type: Article