Big data applications in operations/supply-chain management: A literature review

By R. Addo-Tenkorang, Petri T. Helo. Computers & industrial engineering, 2016

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Big data analytics in supply chain management: A state-of-the-art literature review (2017, background): “A literature review that takes a broad perspective of SC as a whole and cross-maps with BDA techniques in SCM is yet scarce (Olson, 2015; Addo-Tenkorang and Helo, 2016; Hazen et al., 2016; Wang et al., 2016; Mishra et al., 2016).”
Big data analytics in supply chain management between 2010 and 2016: Insights to industries (2018, background): “The study of big data is continuously evolved and expanded, and the main attributes of big data are now expanded into “5V” concept consist of volume, velocity, variety, verification/veracity, and value (White, 2012; Addo-Tenkorang & Helo, 2016).”
The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics (2018, methodology): “Recent surveys by Sha ﬁ q et al. (2015), Addo-Tenkorang and Helo (2016), Richey et al. (2016), Oesterreich and Teuteberg (2016), Küpper et al. (2016), Schrauf and Berttram (2016), Gunasekaran et al. (2016, 2017), Nguyen et al. (2017), Moghaddam and Nof (2017), Hofmann and Rüsch (2017), Choi,…”
The adoption of digital technologies in supply chains: Drivers, process and impact (2021, methodology): “SCM includes the control, management and improvement of the flows of materials and information between the initial suppliers and end users through a network of connected organisations (Christopher 2016).”