Theoretical Analysis of Life Cycle Optimization of Materials Using Artificial Intelligence and Big Data Technologies: Reuse Strategies in the Circular Economy
This study emphasizes the revolution represented by the integration of Artificial Intelligence (AI) and Big Data in sustainability and resource efficiency. These technologies improve materials management and foster innovative reuse strategies, essential for the transition to a circular economy. The...
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| Lenguaje: | español |
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Universidad Francisco de Paula Santander
2024
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| Acceso en línea: | https://revistas.ufps.edu.co/index.php/profundidad/article/view/4543 |
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| _version_ | 1868458539261886464 |
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| author | Silva Aragon, Julio Andres Manzano Duran, Omaira Gonzalez Castro, Yolanda |
| author_browse | Gonzalez Castro, Yolanda Manzano Duran, Omaira Silva Aragon, Julio Andres |
| author_facet | Silva Aragon, Julio Andres Manzano Duran, Omaira Gonzalez Castro, Yolanda |
| author_sort | Silva Aragon, Julio Andres |
| collection | DSPACE IDEP |
| description | This study emphasizes the revolution represented by the integration of Artificial Intelligence (AI) and Big Data in sustainability and resource efficiency. These technologies improve materials management and foster innovative reuse strategies, essential for the transition to a circular economy. The study uses a qualitative grounded theory approach implementing techniques such as literature review and document analysis. The results highlight the need for a multidisciplinary approach in the integration of advanced technologies, combining technical skills with a deep understanding of business models and market dynamics, continuous education and training in AI and Big Data, as well as collaboration between companies, educational institutions and government entities are essential to promote innovation and adoption of these technologies in the circular economy. Finally, we conclude on the importance of integrating advanced technologies in materials management and the need for a holistic approach that combines technological innovations with changes in business models and management practices, emphasizing interdisciplinary collaboration and adaptation to specific contexts to face sustainability challenges. |
| first_indexed | 2026-06-19T15:28:40Z |
| format | Online |
| id | oai:revistas.ufps.edu.co:article-4543 |
| institution | IDEP |
| language | spa |
| last_indexed | 2026-06-19T15:28:40Z |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | Universidad Francisco de Paula Santander |
| publisherStr | Universidad Francisco de Paula Santander |
| record_format | ojs |
| spelling | oai:revistas.ufps.edu.co:article-45432024-10-28T12:08:55Z Theoretical Analysis of Life Cycle Optimization of Materials Using Artificial Intelligence and Big Data Technologies: Reuse Strategies in the Circular Economy Análisis Teórico de la Optimización del Ciclo de Vida de Materiales mediante Tecnologías de Inteligencia Artificial y Big Data: Estrategias de Reutilización en la Economía Circular Silva Aragon, Julio Andres Manzano Duran, Omaira Gonzalez Castro, Yolanda Economía Circular Inteligencia Artificial (IA) Big Data Sostenibilidad Gestión de Materiales Inteligencia de Negocios (BI) Estrategias de Reutilización Modelos de Negocio Sostenibles Circular Economy Artificial Intelligence (AI) Big Data Sustainability Materials Management Business Intelligence (BI) Reuse Strategies Sustainable Business Models This study emphasizes the revolution represented by the integration of Artificial Intelligence (AI) and Big Data in sustainability and resource efficiency. These technologies improve materials management and foster innovative reuse strategies, essential for the transition to a circular economy. The study uses a qualitative grounded theory approach implementing techniques such as literature review and document analysis. The results highlight the need for a multidisciplinary approach in the integration of advanced technologies, combining technical skills with a deep understanding of business models and market dynamics, continuous education and training in AI and Big Data, as well as collaboration between companies, educational institutions and government entities are essential to promote innovation and adoption of these technologies in the circular economy. Finally, we conclude on the importance of integrating advanced technologies in materials management and the need for a holistic approach that combines technological innovations with changes in business models and management practices, emphasizing interdisciplinary collaboration and adaptation to specific contexts to face sustainability challenges. El presente estudio enfatiza la revolución que supone la integración de la Inteligencia Artificial (IA) y Big Data en la sostenibilidad y eficiencia de recursos. Estas tecnologías mejoran la gestión de materiales y fomentan estrategias innovadoras de reutilización, esenciales para la transición hacia una economía circular. El estudio emplea un enfoque cualitativo de tipo teoría fundamentada implementando técnicas como revisión de literatura y análisis de documentos. En los resultados se destaca la necesidad de un enfoque multidisciplinario en la integración de tecnologías avanzadas, combinando habilidades técnicas con una comprensión profunda de los modelos de negocio y dinámicas del mercado, la educación y formación continua en IA y Big Data, así como la colaboración entre empresas, instituciones educativas y entidades gubernamentales son fundamentales para fomentar la innovación y adopción de estas tecnologías en la economía circular. Finalmente, se concluye sobre la importancia de integrar tecnologías avanzadas en la gestión de materiales y la necesidad de un enfoque holístico que combine innovaciones tecnológicas con cambios en modelos de negocio y prácticas de gestión, enfatizando la colaboración interdisciplinaria y la adaptación a contextos específicos para enfrentar los desafíos de sostenibilidad. Universidad Francisco de Paula Santander 2024-07-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf text/html text/xml https://revistas.ufps.edu.co/index.php/profundidad/article/view/4543 10.22463/24221783.4543 Revista Científica Profundidad Construyendo Futuro; Vol. 21 No. 21 (2024): Julio-Diciembre; 123-139 Revista Científica Profundidad Construyendo Futuro; Vol. 21 Núm. 21 (2024): Julio-Diciembre; 123-139 2422-2518 spa https://revistas.ufps.edu.co/index.php/profundidad/article/view/4543/5912 https://revistas.ufps.edu.co/index.php/profundidad/article/view/4543/5913 https://revistas.ufps.edu.co/index.php/profundidad/article/view/4543/5914 /*ref*/Ametller, D. C. (2019). The rulemaking process before technological advance and digital transformation (artificial intelligence social networks and Big Data ). Revista General de Derecho Administrativo, 2019(50). URL: https://www.iustel.com/v2/revistas/detalle_revista.asp?id_noticia=421169&d=1 /*ref*/Arias-Meza, M., Alvarez-Risco, A., Cuya-Velásquez, B. B., Gómez-Prado, R., de las Mercedes Anderson-Seminario, M., & Del-Aguila-Arcentales, S. (2023). Theory of Sustainable Paths for Entrepreneurship Associated with Fashion and Practical Examples. En Environmental Footprints and Eco-Design of Products and Processes (pp. 89-116). https://cris.usil.edu.pe/en/publications/theory-of-sustainable-paths-for-entrepreneurship-associated-with- /*ref*/Betancourt Morales, C. M., & Zartha Sossa, J. W. (2020). Circular economy in Latin America: A systematic literature review. Business Strategy and the Environment, 29(6), 2479-2497. URL: https://doi.org/10.1002/bse.2515 /*ref*/Bohorquez-Lopez, V. W. (2022). Digital transformation in crisis situations. Literature review using topic modeling and grounded theory. Cuadernos de Administracion, 35(1). https://doi.org/10.11144/Javeriana.cao35.tdscrl. /*ref*/Carrión, J. R. H. (2022). Deconstructing the “peer-to-peer sharing economy”: The challenge of the collaborative economy to platform co-operatives in the post-labor age of the 21st Century. CIRIEC-Espana Revista de Economia Publica Social y Cooperativa, 105, 177-204. https://doi.org/10.7203/CIRIEC-E.105.17784. /*ref*/Ferreira, I. A., Godina, R., Pinto, A., Pinto, P., & Carvalho, H. (2023). Boosting additive circular economy ecosystems using blockchain: An exploratory case study. Computers and Industrial Engineering, 175, 108916. https://doi.org/10.1016/j.cie.2022.108916. /*ref*/Franz, N. M., & da Silva, C. L. (2022). Waste Electrical and Electronic Equipment (WEEE): Global and contemporary challenge to production chains and the urban environment. Gestao e Producao, 29(e6621). https://doi.org/10.1590/1806-9649-2022v29e6621. /*ref*/Gil-Lamata, M., & Latorre-Martínez, M. P. (2022). The Circular Economy and Sustainability: A Systematic Literature Review. Cuadernos de Gestion, 22(1), 129-142. https://doi.org/10.5295/CDG.211492MG. /*ref*/Hamam, M., et al. (2021). Circular economy models in agro-food systems: A review. Sustainability (Switzerland), 13(6), 3453. URL: https://doi.org/10.3390/su13063453 /*ref*/Liu, Q., Yang, L., & Yang, M. (2021). Digitalisation for water sustainability: Barriers to implementing circular economy in smart water management. Sustainability (Switzerland), 13(21), 11868. https://doi.org/10.3390/su132111868. /*ref*/Sousa, M. J., & Rocha, Á. (2019). Skills for disruptive digital business. Journal of Business Research, 94, 257-263. URL: https://www.sciencedirect.com/science/article/abs/pii/S0148296317305544?via%3Dihub /*ref*/Zukaib, U., Cui, X., Hassan, M., Harris, S., Hadi, H. J., & Zheng, C. (2023). Blockchain and Machine Learning in EHR Security: A Systematic Review. IEEE Access, 11, 130230-130256. https://doi.org/10.1109/ACCESS.2023.3333229. Derechos de autor 2024 Universidad Francisco de Paula Santander https://creativecommons.org/licenses/by-nc/4.0 |
| spellingShingle | Economía Circular Inteligencia Artificial (IA) Big Data Sostenibilidad Gestión de Materiales Inteligencia de Negocios (BI) Estrategias de Reutilización Modelos de Negocio Sostenibles Circular Economy Artificial Intelligence (AI) Big Data Sustainability Materials Management Business Intelligence (BI) Reuse Strategies Sustainable Business Models Silva Aragon, Julio Andres Manzano Duran, Omaira Gonzalez Castro, Yolanda Theoretical Analysis of Life Cycle Optimization of Materials Using Artificial Intelligence and Big Data Technologies: Reuse Strategies in the Circular Economy |
| title | Theoretical Analysis of Life Cycle Optimization of Materials Using Artificial Intelligence and Big Data Technologies: Reuse Strategies in the Circular Economy |
| title_alt | Análisis Teórico de la Optimización del Ciclo de Vida de Materiales mediante Tecnologías de Inteligencia Artificial y Big Data: Estrategias de Reutilización en la Economía Circular |
| title_full | Theoretical Analysis of Life Cycle Optimization of Materials Using Artificial Intelligence and Big Data Technologies: Reuse Strategies in the Circular Economy |
| title_fullStr | Theoretical Analysis of Life Cycle Optimization of Materials Using Artificial Intelligence and Big Data Technologies: Reuse Strategies in the Circular Economy |
| title_full_unstemmed | Theoretical Analysis of Life Cycle Optimization of Materials Using Artificial Intelligence and Big Data Technologies: Reuse Strategies in the Circular Economy |
| title_short | Theoretical Analysis of Life Cycle Optimization of Materials Using Artificial Intelligence and Big Data Technologies: Reuse Strategies in the Circular Economy |
| title_sort | theoretical analysis of life cycle optimization of materials using artificial intelligence and big data technologies reuse strategies in the circular economy |
| topic | Economía Circular Inteligencia Artificial (IA) Big Data Sostenibilidad Gestión de Materiales Inteligencia de Negocios (BI) Estrategias de Reutilización Modelos de Negocio Sostenibles Circular Economy Artificial Intelligence (AI) Big Data Sustainability Materials Management Business Intelligence (BI) Reuse Strategies Sustainable Business Models |
| topic_facet | Economía Circular Inteligencia Artificial (IA) Big Data Sostenibilidad Gestión de Materiales Inteligencia de Negocios (BI) Estrategias de Reutilización Modelos de Negocio Sostenibles Circular Economy Artificial Intelligence (AI) Big Data Sustainability Materials Management Business Intelligence (BI) Reuse Strategies Sustainable Business Models |
| url | https://revistas.ufps.edu.co/index.php/profundidad/article/view/4543 |
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