Big data analytics in supply chain management between 2010 and 2016: Insights to industries

By Sunil Tiwari, Hui-Ming Wee, Yosef Daryanto. Computers & industrial engineering, 2018

508 citations recorded by the source corpus.

Subfields: Management Information Systems, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/59b53ae2f0ed5ec5c5b86834834fdd406a09a4ef

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management Information Systems

1. Ming-Dung Fu
2. Miying Yang
3. Zihan Zhang

In Management Science and Operations Research

1. Joe Naoum-Sawaya
2. John Gerard Breslin
3. Bissan Ghaddar
4. Claudio Gambella

Citations in the corpus

• The adoption of digital technologies in supply chains: Drivers, process and impact (2021, background): “This is crucial for firms to gain a competitive advantage, because an accurate prediction of market demands and production could massively reduce time and cost, and improve operational efficiency (Min, 2010; Tiwari et al., 2018).”
• Optimization Models for Machine Learning: A Survey (2019, background): “, healthcare, supply chain management [199], marketing, logistics [209], Internet of Things).”
• Big data and stream processing platforms for Industry 4.0 requirements mapping for a predictive maintenance use case (2020, background): “…Corp. have developed smart factories which are based on the powerful capacity of handling big data from different sources, e.g., instruments, sensors, Internet transactions, CAD models, and digital records to enable the real-time control of multiple elements within the production process [11].”