The purpose of this research is to investigate the contingent adoption of Additive Manufacturing (AM) and propose a typology to evaluate its adoption viability within a firm's supply chain.
By conducting semi-structured interviews of practitioners with deep knowledge of AM and supply chains from diverse industries, this research explores the contingent factors influencing AM adoption and their interaction.
While the AM literature is growing, there is a lack of research investigating how contingent factors influence AM adoption. By reviewing the extant literature on the benefits and barriers of AM, we explain the underlying contingencies that enact them. Further, we use an exploratory approach to validate and uncover underexplored contingent factors that influence AM adoption and group them into technological, organizational and strategic factors. By anchoring to a selected set of contingent factors, a typological framework is developed to explain when and how AM is a viable option.
This study focuses on specific industries such as automotive, machine manufacturing, aerospace and defense. Scholars are encouraged to explore the contextual factors affecting AM adoption in particular industries to expand our findings. The authors also acknowledge that the robustness of their framework can be enhanced by integrating the remaining contingent factors.
The developed typological framework provides a pathway for practitioners to see how and when AM can be useful in their supply chains.
This is the first paper in the supply chain management literature to synthesize contingent factors and identify some overlooked factors for AM adoption. The research is also unique in explaining the interaction among selected factors to provide a typological framework for AM adoption. This research provides novel insights for managers to understand when and where to adopt AM and the key contingent factors involved in AM adoption.
We acknowledge the infrastructure and support of Center for Agile and Adaptive Additive Manufacturing (CAAAM) funded through State of Texas Appropriation #190405-105-805008-220 at the University of North Texas, Denton.
Patil, H., Niranjan, S., Narayanamurthy, G. and Narayanan, A. (2022), "Investigating contingent adoption of additive manufacturing in supply chains", International Journal of Operations & Production Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJOPM-05-2022-0286
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