The impact of business analytics on supply chain performance

By Peter Trkman, Kevin McCormack, Marcos Paulo Valadares de Oliveira, Marcelo Bronzo Ladeira. Decision Support Systems, 2010

521 citations recorded by the source corpus.

Subfields: Management Information Systems

View Paper: https://www.semanticscholar.org/paper/60eb2c50041594544fce0980d610625afaa6941f

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In Management Information Systems

Citations in the corpus

An integrated big data analytics-enabled transformation model: Application to health care (2018, background): “…example, IT infrastructure, operational, and managerial bene ﬁ ts have been reported in some of the existing business analytics studies (e.g., [34,36]), and strategic bene ﬁ ts such as speed to market, improved business understanding, and reputation have been mentioned in Wixom et al. ’ s [19]…”
Big data analytics in supply chain management between 2010 and 2016: Insights to industries (2018, background): “Business analytics using information system support has a strong relationship to supply chain performance (Trkman et al., 2010).”
Big data analytics in logistics and supply chain management: Certain investigations for research and applications (2016, unknown): “From the literature review we conducted, we demonstrated the diversity of methodologies and techniques related to LSCM strategy and operations that relate to prescriptive, predictive, and descriptive analytics (Trkman et al., 2010; Delen and Demirkan, 2013; Souza, 2014).”
Impact of Industry 4.0 on supply chain performance (2020, background): “These technological innovations, through quick and advanced analysis of data, can provide insights for substantial performance improvements within supply chain processes (Wamba et al. 2017; Nelissen and Schip 2014; de Oliveira, McCormack and Trkman 2012; Trkman et al. 2010).”
A unified foundation for business analytics (2014, background): “Davenport et al. [21] offers several specific predictions about this, including big data analytics changing the information technology landscape, fast growth of cloud-based predictive analytics, rise of analytics asset management as a major challenge, methods of text and social media analytics…”
Mitigating Supply Chain Risk via Sustainability Using Big Data Analytics: Evidence from the Manufacturing Supply Chain (2017, background): “Researchers categorize big data analytics into descriptive, predictive, and prescriptive [5,11,36].”
Big Data and supply chain management: a review and bibliometric analysis (2016, background): “Several studies (Chae and Olson 2013; Hazen et al. 2014; Trkman et al. 2010) have been conducted on the use of data and analytical capabilities for SCM, focusing mainly on the application and impact of traditional data sources and analytical techniques in supply chain planning and execution.”