Big data analytics (BDA) has captured growing research interests in operations and supply chain management literature, yet, despite the significant implication, extant knowledge falls short in drawing the link between BDA and supply chain planning (SCP) with in a structured manner. This paper employs the Delphi technique to uncover the synergies between BDA technology, conceptualized as big data sources and BDA methods, and the SCP activities framed with the SCP matrix. The panel runs for three rounds with 35 experts including scholars, supply chain practitioners, and BDA specialists. The results of this paper suggest that the relevance of BDA depends on the focal SCP activity. Thirty-five projections are presented on the expected impact of BDA on SCP that are classified into three groups based on the significance of impact and probability of occurrence. This work advances the understanding of BDA in supply chain management drawing implications to prioritize BDA investment for SCP.

Unfolding the link between big data analytics and supply chain planning

Jinou Xu;margherita pero;margherita fabbri
2023-01-01

Abstract

Big data analytics (BDA) has captured growing research interests in operations and supply chain management literature, yet, despite the significant implication, extant knowledge falls short in drawing the link between BDA and supply chain planning (SCP) with in a structured manner. This paper employs the Delphi technique to uncover the synergies between BDA technology, conceptualized as big data sources and BDA methods, and the SCP activities framed with the SCP matrix. The panel runs for three rounds with 35 experts including scholars, supply chain practitioners, and BDA specialists. The results of this paper suggest that the relevance of BDA depends on the focal SCP activity. Thirty-five projections are presented on the expected impact of BDA on SCP that are classified into three groups based on the significance of impact and probability of occurrence. This work advances the understanding of BDA in supply chain management drawing implications to prioritize BDA investment for SCP.
2023
Big data analytics, Supply chain planning, Delphi, Projection, Cluster analysis
File in questo prodotto:
File Dimensione Formato  
1-s2.0-S0040162523004900-main.pdf

accesso aperto

Descrizione: 1-s2.0-S0040162523004900
: Publisher’s version
Dimensione 4.09 MB
Formato Adobe PDF
4.09 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1249138
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 3
  • ???jsp.display-item.citation.isi??? 0
social impact