An Integrated Big Data Analytics Architecture for Resilience: A Case Study of Last-Mile Agri-Food Delivery

Morteza Alaeddini () and Alireza Asgari
Additional contact information
Morteza Alaeddini: AUT - Amirkabir University of Technology, UGA - Université Grenoble Alpes, CERAG - Centre d'études et de recherches appliquées à la gestion - UGA - Université Grenoble Alpes, ICN Business School, CEREFIGE - Centre Européen de Recherche en Economie Financière et Gestion des Entreprises - UL - Université de Lorraine
Alireza Asgari: UGA INP IAE - Grenoble Institut d'Administration des Entreprises - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes, CERAG - Centre d'études et de recherches appliquées à la gestion - UGA - Université Grenoble Alpes

Post-Print from HAL

Abstract: In the wake of global crises and the rising need for robust supply chains, this study delves into the role of big data analytics in agrifood logistics. Emphasizing the need for uninterrupted access to essential food supplies, we use a case study approach to outline the requirements for a comprehensive big data solution. This solution, which includes descriptive, predictive, and prescriptive analytics, is based on industry standards, academic research, and the specific needs of a large B2B2C last-mile food delivery company. The proposed system architecture enhances resilience by integrating these three types of analytics, enabling improved anticipation, response, and recovery from supply chain disruptions.

Keywords: Agri-food supply chain Big data analytics Last-mile delivery Social-ecological resilience Sustainability System architecture Agri-food supply chain Big data analytics Last-mile delivery Social-ecological resilience Sustainability System architecture; Agri-food supply chain; Big data analytics; Last-mile delivery; Social-ecological resilience; Sustainability; System architecture Agri-food supply chain; System architecture (search for similar items in EconPapers)
Date: 2025
New Economics Papers: this item is included in nep-agr
Note: View the original document on HAL open archive server: https://hal.science/hal-05045283v1
References: View references in EconPapers View complete reference list from CitEc
Citations:

Published in Procedia Computer Science, 2025, 253, pp.1621 - 1630. ⟨10.1016/j.procs.2025.01.224⟩

Downloads: (external link)
https://hal.science/hal-05045283v1/document (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05045283

DOI: 10.1016/j.procs.2025.01.224

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().