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Digital Transformation and Supply Chain Efficiency: A Case of Amazon Inc

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  • Emmanuel Olusegun Alalade

    (Department of Business Administration, New Mexico Highlands University, Las Vegas, NM 87701, United States of America)

Abstract

This study investigates the relationship between digital transformation (DT) and supply chain efficiency (SCE) at Amazon Inc., utilizing Structural Equation Modeling (SEM) to analyze data collected from the company’s annual reports. Digital transformation was measured using three key proxies: digital transformation disclosures (DTD), the digital assets ratio (DAR), and cloud services revenue (CSR), while SCE was assessed through inventory turnover. The study aimed to determine the extent to which digital transformation contributes to supply chain optimization, framed within the resource-based view (RBV) theory. The findings revealed a positive relationship between DT and SCE, with a path coefficient of 0.664. However, the p-value of 0.235 suggests this relationship is not statistically significant, indicating that additional factors may mediate or moderate the effect of DT on SCE. The results reveal that while DT initiatives which includes rtificial intelligence, big data, and cloud computing, improve operational processes, their impact on SCE may depend on organizational context and the consistency of their implementation. The study concludes that achieving supply chain efficiency through digital transformation requires a comprehensive approach that integrates technology, organizational culture, and strategic alignment. It recommends future research to explore additional mediating factors and longitudinal analyses to deepen the understanding of DT’s impact on supply chain performance. These findings provide valuable insights for practitioners and scholars in digital transformation and supply chain management.

Suggested Citation

  • Emmanuel Olusegun Alalade, 2024. "Digital Transformation and Supply Chain Efficiency: A Case of Amazon Inc," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(12), pages 3931-3944, December.
    • Handle: RePEc:bcp:journl:v:8:y:2024:i:12:p:3931-3944
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    References listed on IDEAS

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    1. Lianju Ning & Dan Yao, 2023. "The Impact of Digital Transformation on Supply Chain Capabilities and Supply Chain Competitive Performance," Sustainability, MDPI, vol. 15(13), pages 1-22, June.
    2. Verhoef, Peter C. & Broekhuizen, Thijs & Bart, Yakov & Bhattacharya, Abhi & Qi Dong, John & Fabian, Nicolai & Haenlein, Michael, 2021. "Digital transformation: A multidisciplinary reflection and research agenda," Journal of Business Research, Elsevier, vol. 122(C), pages 889-901.
    3. Lei Guo & Luying Xu, 2021. "The Effects of Digital Transformation on Firm Performance: Evidence from China’s Manufacturing Sector," Sustainability, MDPI, vol. 13(22), pages 1-18, November.
    4. Russell Allgor & Tolga Cezik & Daniel Chen, 2023. "Algorithm for Robotic Picking in Amazon Fulfillment Centers Enables Humans and Robots to Work Together Effectively," Interfaces, INFORMS, vol. 53(4), pages 266-282, July.
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