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Efficiency and Performance of Big Data Analytics for Supply Chain Management

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  • Elena PUICA

Abstract

This paper aims to clarify the problem of Supply Chain Management (SCM) efficiency in the context of universal theoretical reflections relating to SCM and analyze the correlation be-tween Big Data Analytics and the efficiency and performance of the supply chain. An adequate SCM has to be cost-effective (economic efficiency), functional (reducing processes, minimizing the number of links in the SCM to the necessary ones), and ensuring high quality of services and products (customer-oriented logistics systems). The efficiency of SCM is not only an activity for which the logistics department is in charge, as it is a strategic decision taken by the man-agement regarding the method of future company operation. Correctly organized and fulfilled logistics tasks may advance the performance of an organization and the whole SCM. Essential enhancements in SCM efficiency may be ensured by analyzing theoretical models on the strate-gic level and implementing a selected concept.

Suggested Citation

  • Elena PUICA, 2022. "Efficiency and Performance of Big Data Analytics for Supply Chain Management," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 26(1), pages 16-24.
    • Handle: RePEc:aes:infoec:v:26:y:2022:i:1:p:16-24
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    References listed on IDEAS

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    1. Wang, Yulan & Wallace, Stein W. & Shen, Bin & Choi, Tsan-Ming, 2015. "Service supply chain management: A review of operational models," European Journal of Operational Research, Elsevier, vol. 247(3), pages 685-698.
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