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Big Data and Predictive Analysis is Key to Superior Supply Chain Performance: A South African Experience

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  • Surajit Bag

    (Tega Industries (PTY) Ltd, Gauteng, South Africa)

Abstract

The study considers samples from the South African engineering companies who are strategic suppliers to mining and minerals industry and further explores the uncertainties persisting in the supply chain network. Further investigation was done to understand the role of big data and predictive analysis (BDPA) in managing the supply uncertainties. The paper finally uses partial least square regression analysis to study the relationship among buyer-supplier relationship, big data and predictive analysis and supply chain performance. The analysis supported the second and third hypothesis. Therefore, it is established that firstly, there is a positive relationship between big data, predictive analysis and supply chain performance and secondly, there is a positive relationship between and big data, predictive analysis and buyer-supplier relationship. The study is a unique contribution to the current literature by shedding light on the practical problems persisting in the South African context.

Suggested Citation

  • Surajit Bag, 2017. "Big Data and Predictive Analysis is Key to Superior Supply Chain Performance: A South African Experience," International Journal of Information Systems and Supply Chain Management (IJISSCM), IGI Global, vol. 10(2), pages 66-84, April.
  • Handle: RePEc:igg:jisscm:v:10:y:2017:i:2:p:66-84
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    Cited by:

    1. J. Piet Hausberg & Kirsten Liere-Netheler & Sven Packmohr & Stefanie Pakura & Kristin Vogelsang, 2019. "Research streams on digital transformation from a holistic business perspective: a systematic literature review and citation network analysis," Journal of Business Economics, Springer, vol. 89(8), pages 931-963, December.
    2. Yang, Miying & Fu, Mingtao & Zhang, Zihan, 2021. "The adoption of digital technologies in supply chains: Drivers, process and impact," Technological Forecasting and Social Change, Elsevier, vol. 169(C).

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