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Does Supply Chain Analytics Enhance Supply Chain Innovation and Robustness Capability?

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  • Shamout Mohamed Dawood

    (The American University in the Emirates, College of Business Administration)

Abstract

Background and purpose: Little are known about the nature of the interaction between supply chain analytics, supply chain innovation and robustness capability. The purpose of this paper is to examine the effectiveness of supply chain analytics in enhancing firms supply chain innovation and robustness capability in the Arabian context.Design/Methods: Using knowledge-based view and survey data from line managers in supply and logistics departments, the present study uses variance-based structural equation modeling (PLS-SEM) to diagnose the association between supply chain analytics, supply chain innovation and robustness capability.Findings: Results suggest that supply chain analytics exerted significant impact on supply chain innovation and not on robustness capability. It appears that supply chain innovation exerted a significant impact on robustness capability, in doing so, supply chain innovation mediates the link supply chain analytics and robustness capability.Conclusion: The outcome of this study points to the importance of supply chain analytics as a functional tool for supply chain and/or logistic routes stability and success. The paper concludes supply chain analytics can help managers have access timely and useful data for greater innovation; and that supply chain innovation is reliant not only on data, but also on firms’ analytic capabilities.

Suggested Citation

  • Shamout Mohamed Dawood, 2019. "Does Supply Chain Analytics Enhance Supply Chain Innovation and Robustness Capability?," Organizacija, Sciendo, vol. 52(2), pages 95-106, May.
  • Handle: RePEc:vrs:organi:v:52:y:2019:i:2:p:95-106:n:2
    DOI: 10.2478/orga-2019-0007
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    Cited by:

    1. Kalaitzi, Dimitra & Tsolakis, Naoum, 2022. "Supply chain analytics adoption: Determinants and impacts on organisational performance and competitive advantage," International Journal of Production Economics, Elsevier, vol. 248(C).
    2. Weihua Liu & Siyu Wang & Jingkun Wang, 2023. "Evaluation method of path selection for smart supply chain innovation," Annals of Operations Research, Springer, vol. 322(1), pages 167-193, March.

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