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resumen

Resumen
The bioeconomy is an evolving concept that faces measurement challenges due to the scarcity of up-to-date, structured, and comprehensive data. We argue that digital technologies—including artificial intelligence (AI), machine learning (ML), automation, sensors and biosensors, blockchain and the Internet of Things (IoT)—can enhance the bioeconomy measurement. However, there is currently no clear evidence linking the elements of the cyber-physical social [ver mas...]
dc.contributor.authorLeavy, Sebastian
dc.contributor.authorAllegretti, Gabriela
dc.contributor.authorPresotto, Elen
dc.contributor.authorMontoya, Marco Antonio
dc.contributor.authorTalamini, Edson
dc.date.accessioned2026-02-13T12:00:13Z
dc.date.available2026-02-13T12:00:13Z
dc.date.issued2026-03
dc.identifier.issn0160-791X
dc.identifier.issn1879-3274
dc.identifier.otherhttps://doi.org/10.1016/j.techsoc.2025.103101
dc.identifier.urihttp://hdl.handle.net/20.500.12123/25199
dc.identifier.urihttps://www.sciencedirect.com/science/article/abs/pii/S0160791X2500291X
dc.description.abstractThe bioeconomy is an evolving concept that faces measurement challenges due to the scarcity of up-to-date, structured, and comprehensive data. We argue that digital technologies—including artificial intelligence (AI), machine learning (ML), automation, sensors and biosensors, blockchain and the Internet of Things (IoT)—can enhance the bioeconomy measurement. However, there is currently no clear evidence linking the elements of the cyber-physical social system (CPSS) within the conceptual scopes of the bioeconomy. So, this study explores the convergence between digital technologies and the conceptual elements of bioeconomy. Firstly, independent literature reviews were conducted using Biblioshiny, VOSviewer, QDA Miner and WordStat to (i) define the core terms in the scope of bioeconomy concepts and (ii) map the digital technologies. Secondly, we coded and analyzed the literature content with QDA Miner and WordStat to examine the co-occurrence of digital technologies and the conceptual elements of the bioeconomy. The results indicate that the Biomass-Based Bioeconomy (BmBB), Biotechnology-Based Bioeconomy (BtBB), and Biosphere-Based Bioeconomy (BsBB) possess distinct clusters of conceptual elements but also integrative domains, like metabolism. Our findings reveal that digital technologies within categories of data science and analytics, computing and software, and imaging and sensing have been the most prevalent in the bioeconomy context. Evidence has surfaced regarding the interactions between the bioeconomy concepts and digital technologies, illustrating the role of digitization in enhancing data collection, storage, processing and communication across various aspects of the bioeconomy. This evidence underscores the potential of digitalization for a comprehensive measure of the bioeconomy. Ultimately, this research provides valuable insights for improving bioeconomy assessment and supports sustainability goals by integrating emerging digital technologies with the bioeconomy development.eng
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.publisherElsevieres_AR
dc.rightsinfo:eu-repo/semantics/restrictedAccesses_AR
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/es_AR
dc.sourceTechnology in Society 84 : 103101. (March 2026)es_AR
dc.subjectBioeconomíaes_AR
dc.subjectBioeconomyeng
dc.subjectSostenibilidades_AR
dc.subjectSustainabilityeng
dc.subjectTecnología Digitales_AR
dc.subjectDigital Technologyeng
dc.subjectInteligencia Artificiales_AR
dc.subjectArtificial Intelligenceeng
dc.subject.otherSustentabilidades_AR
dc.titleTowards digitalization for comprehensive measurement of the bioeconomy: exploring the convergence between elements of the cyber-physical social systemes_AR
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articlees_AR
dc.typeinfo:eu-repo/semantics/publishedVersiones_AR
dc.rights.licenseCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)es_AR
dc.description.origenEEA Pergaminoes_AR
dc.description.filFil: Leavy, Sebastián. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Agencia de Extensión Rural Vedia; Argentinaes_AR
dc.description.filFil: Leavy, Sebastián. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Cátedra de Comercialización Agropecuaria; Argentinaes_AR
dc.description.filFil: Leavy, Sebastián. Universidad de Federal do Rio Grande do Sul. Centro de Estudios e pesquisas en Agronegocios. Grupo de investigación en Bioeconomía; Brasiles_AR
dc.description.filFil: Allegretti, Gabriela. Universidad de Federal do Rio Grande do Sul. Centro de Estudios e pesquisas en Agronegocios. Grupo de investigación en Bioeconomía; Brasiles_AR
dc.description.filFil: Allegretti, Gabriela. Instituto Brasileño de Bioeconomía; Brasiles_AR
dc.description.filFil: Allegretti, Gabriela. Universidad de Rio Verde. Administración de Empresas; Brasiles_AR
dc.description.filFil: Presotto, Elen. Universidad de Brasilia. Facultad de Agronomía y Medicina Veterinaria; Brasiles_AR
dc.description.filFil: Montoya, Marco Antonio. Universidad de Passo Fundo. Facultad de Economía, Gestión y Contabilidad. Grupo de Investigación en Economía y Gestión de Agronegocios; Brasiles_AR
dc.description.filFil: Talamini, Edson. Universidad de Federal do Rio Grande do Sul. Centro de Estudios e pesquisas en Agronegocios. Grupo de investigación en Bioeconomía; Brasiles_AR
dc.description.filFil: Talamini, Edson. Instituto Brasileño de Bioeconomía; Brasiles_AR
dc.description.filFil: Talamini, Edson. Universidade Federal do Rio Grande do Sul. Facultad de Economía. Departamento de Economía y Relaciones Internacionales; Brasiles_AR
dc.subtypecientifico


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