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Big data for corporate social responsibility: blockchain use in Gioia del Colle DOP

The traceability of the supply chain with strict compliance with the specification to demonstrate in "transparency" the production processes in compliance with legislation and from a corporate social responsibility perspective, represents a fundamental requirement at the basis of competiti...

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Detalles Bibliográficos
Autores principales: Giacalone, Massimiliano, Santarcangelo, Vito, Donvito, Vincenzo, Schiavone, Oriana, Massa, Emilio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7818064/
https://www.ncbi.nlm.nih.gov/pubmed/33495664
http://dx.doi.org/10.1007/s11135-021-01095-w
Descripción
Sumario:The traceability of the supply chain with strict compliance with the specification to demonstrate in "transparency" the production processes in compliance with legislation and from a corporate social responsibility perspective, represents a fundamental requirement at the basis of competitive advantage in the food industries (Patelli and Mandrioli, J Food Sci 85: 3670–3678, 2020). The purpose of this work is to illustrate the innovative method for the certification and protection of the production phases of the DOP food chain and specifically the Mozzarella DOP of Gioia del Colle produced by the company Capurso Azienda Casearia Srl. This innovative approach consists of several phases that will be described in detail in the following paper. Besides, the idea of the introduction of Blockchain technology in an industry like this is an important step. This technology, associated with more accurate and intelligent management of the data acquisition process (Big data approach), optimizes the productivity of small businesses such as the dairy company. Blockchain technology guarantees security in the management of large amounts of data as never before possible, an innovative and experimental approach that makes the entire path of the production chain more controlled and optimized (Giacalone et al. International workshop on fuzzy logic and applications. Springer, Cham, pp. 218–225, 2016).