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A Classification Predictive Model to Analyze the Supply Chain Strategies


  • Elena PUICA


Big Data Analytics (BDA) has the capacity to increase communications and better manage supply chain strategies. The main objective of this study developed, firstly was a systematic literature review, to understand how BDA has been investigated on supply chain strategies, which resources are handled by BDA and which Supply Chain Management strategies are positively affected by those technologies, and secondly, to apply a classification predictive model to foresee the level of implementation of innovative technologies in supply chain strategies. The applied predictive classification model helped to offer an understanding and to determine that in supply chain strategies there are innovative technologies implemented and their percentage of implementation will have an increasing value. This study, that is focused on BDA and supply chain strategies, offers new opportunities, and is adding value and operational excellence for existing supply chain practices. The adoption of big data technology in supply chain can create considerable value-added.

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  • Elena PUICA, 2021. "A Classification Predictive Model to Analyze the Supply Chain Strategies," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 25(2), pages 29-39.
  • Handle: RePEc:aes:infoec:v:25:y:2021:i:2:p:29-39

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    References listed on IDEAS

    1. Arias, Mariz B. & Bae, Sungwoo, 2016. "Electric vehicle charging demand forecasting model based on big data technologies," Applied Energy, Elsevier, vol. 183(C), pages 327-339.
    2. Souza, Gilvan C., 2014. "Supply chain analytics," Business Horizons, Elsevier, vol. 57(5), pages 595-605.
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