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Harnessing the power of big data digitization for market factors awareness in supply chain management

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A Correction to this article was published on 26 July 2022

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Abstract

An increasing complication due to the rise of dynamic trades and global industry causes a burden in decision-making. There is a need for multi-level perspective factors in supply chain management, such as short-long terms of demand and supply, and their impact on agricultural market dynamics. In this study, Big data is proposed as supply chain open data sensors for data digitization to deal with the problem. Although Big data supports comprehensive, real-time sources, and provides information about market functions, traditional machine learning technologies have proved insufficient for dealing with Big data characteristics. We then propose a time-series decomposition approach for extracting contexts about short-long term impacts to provide insights into Big data for determining market demand and supply. Our agri-big data digitization reveals the significant information about Big data with the better predictive ability and can support agri-big data analysis using any kind of machine learning model.

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Acknowledgement

This work was supported in part by the Thailand Education Hub for ASEAN Scholarship in Doctoral Degree funded by Prince of Songkla University, Thailand under Grant No. TEH-233/2016.

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Authors and Affiliations

  1. Department of Computer Engineering, Faculty of Engineering, Prince of Songkla University, Songkla, Thailand

    Mallika Kliangkhlao & Somchai Limsiroratana

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  1. Mallika Kliangkhlao
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  2. Somchai Limsiroratana
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Correspondence to Mallika Kliangkhlao.

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Kliangkhlao, M., Limsiroratana, S. Harnessing the power of big data digitization for market factors awareness in supply chain management. Multimed Tools Appl 82, 347–365 (2023). https://doi.org/10.1007/s11042-022-13309-w

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  • DOI: https://doi.org/10.1007/s11042-022-13309-w

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