The impact of big data on world-class sustainable manufacturing

By Rameshwar Dubey, Angappa Gunasekaran, Stephen J. Childe, Samuel Fosso Wamba, Thanos Papadopoulos. The International Journal of Advanced Manufacturing Technology, 2015

361 citations recorded by the source corpus.

Subfields: Industrial and Manufacturing Engineering, Management Information Systems, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/4271319294949d4ee6c88b653429af9ab7f58a9b

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In Industrial and Manufacturing Engineering

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Citations in the corpus

Data-driven supply chains, manufacturing capability and customer satisfaction (2017, background): “In other words, DDSC enable the creation of superior manufacturing capabilities, which in turn support higher levels of organisational performance in areas such as customer satisfaction (Dubey et al. 2016).”
Mitigating Supply Chain Risk via Sustainability Using Big Data Analytics: Evidence from the Manufacturing Supply Chain (2017, background): “Thus, scholars acknowledge the need for further exploration in this domain [21,29,30,44].”
Big Data and Predictive Analytics and Manufacturing Performance: Integrating Institutional Theory, Resource‐Based View and Big Data Culture (2019, positive): “Other scholars note the popularity of BDPA tools only amongst manufacturing organizations that seek to improve their complex decision making and their manufacturing quality while reducing support costs by improving defect tracking and forecasting abilities (Dutta and Bose, 2015; Dubey et al., 2016).”
The adoption of digital technologies in supply chains: Drivers, process and impact (2021, background): “A number of studies have suggested that digital technologies could be used to improve supply chain sustainability (Bag et al., 2018; Birkel et al., 2019; Melo et al., 2019; Dubey et al., 2016).”
Big Data and supply chain management: a review and bibliometric analysis (2016, background): “Researchers (Chen et al. 2012; Wamba et al. 2015; Dubey et al. 2016; Wang et al. 2016; Song et al. 2016) have endeavoured to explore different dimensions of Big Data and capture the potential benefits to supply chain management (SCM).”
Big data analytics in supply chain management: A state-of-the-art literature review (2017, background): “, 2017), and data security issues (Fawcett and Waller, 2014; Dubey et al., 2016).”