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Path to Improved Supply Chain Performance: Additive Manufacturing Adoption, Integration, and Responsiveness

  • Changjoon LEE (College of Business Administration, University of Ulsan) ;
  • Soohyo KIM (Logistics, Service, Operations Management, Sogang University)
  • Received : 2024.07.11
  • Accepted : 2024.11.05
  • Published : 2024.11.30

Abstract

Purpose: This study aimed to empirically investigate how additive manufacturing (AM) adoption affects supply chain performance (SCP) through supply chain integration (SCI) and responsiveness. Research and Design Methodology: This study adopted a quantitative research design; data were collected via a survey that targeted a sample of firms that have adopted specific AM technologies. The survey measured AM adoption readiness, SCI, agility, and performance. This study employs structural equation modeling to test the hypothesized relationships among these variables while accounting for firm size, industry, and supply chain complexity. To validate the structural equation model, we utilized 195 survey responses collected from employees working in supply chain-related departments in Korea. Furthermore, we would like to state that SPSS 18.0 and AMOS 18.0 were used for the statistical analysis. Principal Results: Our empirical findings support all four hypotheses, indicating that a higher level of AM adoption stimulates SCI and complementary supply chain responsiveness requirements. The results indicate that AM adoption can improve SCP through the integration and responsiveness. Conclusions: This study contributes to the growing body of knowledge on the strategic implications of AM for supply chain management. The findings highlight the importance of considering AM as a strategic enabler of SCP rather than solely a tactical tool.

Keywords

References

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