A Structural Equation Model For Adopting Additive Manufacturing in the Footwear Firms Supply Chains
DOI:
https://doi.org/10.14488/BJOPM.2322.2025Keywords:
Additive manufacturing, Footwear firms, Structural equation modeling, Supply chain complexityAbstract
Goal: The objective of this research is to present a theoretical framework and explore how additive manufacturing (AM) techniques affect supply chain complexity (SCC) in the footwear sector.
Design/Methodology/Approach: This study developed theoretical framework that includes AM best practices and SCC through extensive literature review. Using 1-5 likert scale surveys, data were gathered from 205 professionals working in 29 Ethiopian footwear industries in the period October 20 to December 23, 2023. The collected questionnaires were tested for reliability and validity, measurement and structural model fit test were checked using confirmatory factor analysis. Structural Equation Modeling using AMOS v23 was used to evaluate the proposed correlations.
Results: The confirmatory factor analysis test result revealeld that measurement and structural equation model fit test fulfill the model fit test requirements, i.e. χ2/df < 5, CFI, GFI and TLI > 0.9, RMR and RMSEA < 0.08. The findigs of the study confirmed that additive manufacturing best practices (time, inventory, operation, and resource, energy and waste related factors) have positive effects on static and dynamic supply chain complexity.
Practical implications: This study helps the firm to focus on adoptation of AM for improving supply chain complexity. Furthermore, this study extended earlier research in the domains of SCM by building a theoretical framework that connects AM best practices with supply chain complexity factors.
Originality/value: This work bridges the scientific knowledge gap by combining supply chain complexity and AM best practices. Among others, it can contribute to the existing literature by illustrating the benefits of adopting AM technology particularly in footwear sector.
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Copyright (c) 2025 Tekalign Lemma, Endalkachew Mosisa Gutema, Hirpa G. Lemu, Mahesh Gopal
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