Big Data Analytics for Supply Chain Management

Moufaddal, Mariam; Benghabrit, Asmaa; Bouhaddou, Imane

doi:10.1007/978-3-319-74500-8_87

Cited by 1 publication

(1 citation statement)

References 40 publications

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“…The research premise considers that the efficient management of an organization across the various operational sub-areas will lead to a sustainable competitive advantage within the area of interest of this research, namely SCM [37].…”

Section: Conclusion and Managerial Implicationsmentioning

confidence: 99%

A Quantitative Analysis of Big Data Analytics Capabilities and Supply Chain Management

Zitianellis

2023

Artificial Intelligence

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With the emergence of Big Data Technologies (BDT) and the growing application of Big Data Analytics (BDA), Supply Chain Management (SCM) researchers increasingly utilize BDA due to the opportunities from BDT and BDA present. Supply Chain (SC) data is inherently complex and results in an environment with high uncertainty, which presents a real challenge for SC decision-makers. This research study aimed to investigate and illustrate the application of BDA within the existing decision-making process. BDT allowed for the extraction and processing of SC data. BDA aided further understanding of SC inefficiencies and delivered valuable, actionable insights by validating the existence of the SC bullwhip phenomenon and its contributing factors. Furthermore, BDA enabled the pragmatic evaluation of linear and nonlinear regression SC relationships by applying machine learning techniques such as Principal Component Analysis (PCA) and multivariable regression analysis. Moreover, applying more sophisticated BDA time series and forecasting techniques such as Sarimax, Tbats, and neural networks improved forecasting accuracy. Ultimately, the improved demand planning and forecast accuracy will reduce SC uncertainty and the effects of the observed SC bullwhip phenomenon, thus creating a competitive advantage for all the members within the SC value chain.

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Section: Conclusion and Managerial Implicationsmentioning

confidence: 99%

A Quantitative Analysis of Big Data Analytics Capabilities and Supply Chain Management

Zitianellis

2023

Artificial Intelligence

View full text Add to dashboard Cite

show abstract

Big Data Analytics for Supply Chain Management

Cited by 1 publication

References 40 publications

A Quantitative Analysis of Big Data Analytics Capabilities and Supply Chain Management

A Quantitative Analysis of Big Data Analytics Capabilities and Supply Chain Management

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