Integration of industry 4.0 technologies for agri-food supply chain resilience
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41210%2F25%3A101820" target="_blank" >RIV/60460709:41210/25:101820 - isvavai.cz</a>
Result on the web
<a href="https://www.webofscience.com/wos/woscc/full-record/WOS:001389382300001" target="_blank" >https://www.webofscience.com/wos/woscc/full-record/WOS:001389382300001</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.compind.2024.104225" target="_blank" >10.1016/j.compind.2024.104225</a>
Alternative languages
Result language
angličtina
Original language name
Integration of industry 4.0 technologies for agri-food supply chain resilience
Original language description
The agri-food supply chain (AFSC) operations are becoming challenging due to globalization, constantly shifting consumer demands, and intensive disruptions leading to inefficient production and distribution of safe and highquality food. Technological advancements are the most promising ways to ensure firms' survival and supply chains. To enhance the resilience of AFSCs, the present study aims to identify and model the challenges associated with AFSC operations in the context of the United Arab Emirates (UAE) food processing industry. An integrated methodology using the Grey Influence Analysis (GINA) and Fuzzy Linguistic Quantifier Ordered Weighted Aggregation (FLQOWA) methodology is applied to analyze resilience enablers and assess industry 4.0 technologies (I4Ts) that can enhance resilience in AFSCs. The GINA technique helps identify the most influential resilience enablers, and the FLQOWA helps assess and prioritize I4Ts to enhance resilient enablers. The findings reveal that out of thirteen sub-enablers, four are the most influential resilient enablers, viz., real-time information sharing, enhanced product traceability, improved risk management, and planning and network design; and out of ten I4Ts, three are the most influential technologies viz., big data analytics, Internet of things, and cloud computing can further enhance resilience enablers. The findings from the study can help AFSC organizations and the government formulate appropriate strategies based on the integrated matrix developed by selecting the best combination of technologies for strengthening the required resilient enablers among the AFSC stakeholders.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20700 - Environmental engineering
Result continuities
Project
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Continuities
R - Projekt Ramcoveho programu EK
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
COMPUTERS IN INDUSTRY
ISSN
0166-3615
e-ISSN
1872-6194
Volume of the periodical
165
Issue of the periodical within the volume
neuvedeno
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
19
Pages from-to
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UT code for WoS article
001389382300001
EID of the result in the Scopus database
2-s2.0-85211753976