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OPEN INNOVATION AND ITS EFFECTS ON ECONOMIC AND SUSTAINABILITY PERFORMANCE FOR THE DIRECT SALE AGRI-FOOD PRODUCTS IN SICILY. THE CASE OF ARTIFICIAL INTELLIGENCE.

Zarb Carla, Chinnici Gaetano, Pappalardo Gioacchino, Matarazzo Agata, Scuderi Alessandro

First published: 2025-12-27https://doi.org/10.5593/sgem2025v/4.2/s20.83View metrics

Abstract

While the transition toward sustainable food systems pose a significant challenge, it also offers substantial economic opportunities. As consumer expectations evolve, the food market is undergoing a profound transformation. This shift presents new prospects for farmers, food processors, catering services, and other stakeholders across the agri-food sector. Pursuing the transition implementation can enable all the domestic food system operators along the agri-food chain to accomplish sustainability and to enrich their brand and potentially gaining a first-mover advantage over foreign competitors. This premise suggested the conduction of the present survey in Sicily, which focuses on food supply chains in Sicily that originate from local farms. These engage in integrated operations such as production, transportation, distribution, and marketing either directly on-site through agritourism, catering, and tasting services, or primarily within nearby local markets. For these food systems, artificial intelligence (AI) represents a promising tool to enhance various operational functions. AI can optimize cultivation practices, thereby improving both product quality and sustainability. Advanced AI methods allow for the automation of increasingly complex agricultural processes.

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Publication details

Title
OPEN INNOVATION AND ITS EFFECTS ON ECONOMIC AND SUSTAINABILITY PERFORMANCE FOR THE DIRECT SALE AGRI-FOOD PRODUCTS IN SICILY. THE CASE OF ARTIFICIAL INTELLIGENCE.
Authors
Zarb Carla, Chinnici Gaetano, Pappalardo Gioacchino, Matarazzo Agata, Scuderi Alessandro
Proceedings
25th International Multidisciplinary Scientific GeoConference Proceedings SGEM 2025, Energy and Clean Technologies
Publisher
STEF92 Technology
Year
2025
Pages
757-760
SWS Citekey
Carla202520757760
ISSN
1314-2704; 13142704
ISBN
9786197603934
Language
en
Publication type
Conference Paper
Proceedings contents
Open official contents
Keywords
Agri-food systemArtificial Intelligencefarmers.
References2

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    View DOICrossrefGoogle ScholarWeb of ScienceScopusOpenCitations

  2. ML How, YJ Chan, SM Cheah (2020) �Predictive insights for improving the resilience of global food security using artificial intelligence�. Sustainability. DOI: 10.3390/su12156272

    View DOICrossrefGoogle ScholarWeb of ScienceScopusOpenCitations
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