An Analytic Model for Quantitatively Assessing the Resilience Level of an Agri-Food Supply Chain: Development and Validation

Letizia Tebaldi (), Amedeo Mattia Gubiotti and Giuseppe Vignali
Additional contact information
Letizia Tebaldi: Department of Engineering for Industrial Systems and Technologies, University of Parma, Parco Area Delle Scienze 181/A, 43124 Parma, Italy
Amedeo Mattia Gubiotti: Department of Engineering for Industrial Systems and Technologies, University of Parma, Parco Area Delle Scienze 181/A, 43124 Parma, Italy
Giuseppe Vignali: Department of Engineering for Industrial Systems and Technologies, University of Parma, Parco Area Delle Scienze 181/A, 43124 Parma, Italy

Sustainability, 2024, vol. 16, issue 24, 1-18

Abstract: Over the last decade, resilience has become an indispensable aspect to be considered when managing supply chains given to the recent challenges they were subjected to, and a constituting element of their sustainability. However, despite literature on supply chain resilience is copious, tools for quantifying the resilience of a business are lacking, especially when dealing with the a priori resilience of a system, since several assessments are a posteriori carried out, after a disruption has manifested. In response, an analytic quantitative model is here proposed, whose output is a Global Resilience Index for a company. The model is divided into 3 phases: Supply (8 factors), Production (12 factors) and Distribution (5 factors); these elements were derived from literature and semi-structured interviews with practitioners. The logical functioning of the model is based on weighted averages attributed to each single factor; for defining the weights a survey was sent, in which respondents had to express their opinion with reference to the perceived impact of those factors on resilience. For validating the model, it was implemented in three companies manufacturing the following products: fresh milk, ginseng coffee and vegetable preserves. Despite none of them reached the higher resilience level, results offer interesting insights for let the users understand where the system is weaker. This model is intended to be made available to those who desire to include the resilience assessment to manage operational decisions; moreover, this value could be included in a wider sustainability assessment of a business.

Keywords: resilience assessment; resilience model; quantitative assessment; Global Resilience Index; food industry; food supply chain; agri-food; resilience factors; resilience indicators; quantitative model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/16/24/11038/pdf (application/pdf)
https://www.mdpi.com/2071-1050/16/24/11038/ (text/html)

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:gam:jsusta:v:16:y:2024:i:24:p:11038-:d:1545164

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().