Data science, predictive analytics, and big data in supply chain management: Current state and future potential

By Tobias Schoenherr, Cheri Speier-Pero. 2015

453 citations recorded by the source corpus.

Subfields: Management Information Systems, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/f6705e68c71bc0b51ddb8d1e4f986c894ba8f34f

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In Management Information Systems

In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

The adoption of digital technologies in supply chains: Drivers, process and impact (2021, background): “Literature has discussed that the adoption at high intelligent technology level (the level C in Figure 3) can help firms respond faster to the changing environment and facilitate the risk management (Büyüközkan and Göçer, 2018; Schoenherr and Speier-Pero, 2015; Wood et al., 2017).”
Researchers' perspectives on Industry 4.0: multi-disciplinary analysis and opportunities for operations management (2020, unknown): “Our approach is similar to the approach presented in Sodhi et al. (2012) and Schoenherr and Speier-Pero (2015).”
Impact of Industry 4.0 on supply chain performance (2020, background): “This, subsequently, can improve order acceptance decision making and allow for better planning throughout the supply chain (Gunasekaran et al. 2017; Schoenherr and Speier-Pero 2015).”
Management challenges in creating value from business analytics (2017, background): “Schoenherr and Speier-Pero (2015) provided a holistic view regarding DPB’s current state and future potential for LSCM while at a more tactical level Hazen et al. (2014) discussed data quality and Bendoly (2016) proposed how to better visualize data through the use of semiotics for sense making.”
Data-driven supply chains, manufacturing capability and customer satisfaction (2017, background): “The ultimate goal being to develop data-driven supply chains (DDSC) (Schoenherr and Speier-Pero 2015).”
Big Data Analytics Capabilities and Innovation: The Mediating Role of Dynamic Capabilities and Moderating Effect of the Environment (2019, unknown): “For instance, a sizeable number of firms now build on big data analytics to support real-time processes orchestration for logistics and supply chain activities (Schoenherr & Speier‐Pero, 2015).”
Big data and predictive analytics for supply chain and organizational performance (2017, methodology): “Schoenherr and Speier-Pero (2015) note that BDPA can assist in reducing supply chain costs and achieving efficiency, responding faster to changing environment, providingmore power in supplier relationships with suppliers and enhancing sales and operations planning capabilities.”