Publicación: La inteligencia artificial como herramienta de apoyo a la toma de decisiones gerenciales en la gestión del cronograma de proyectos
| dc.contributor.advisor | Ochoa Durán, Jaime Alberto | |
| dc.contributor.author | Triana Ávila, Paula Andrea | |
| dc.contributor.author | Zambrano Forero, Karen Lizeth | |
| dc.contributor.author | Fino, Yudi Lizeth | |
| dc.contributor.author | Bobadilla Vanegas, Luisa Fernanda | |
| dc.creator.id | 53160106 | |
| dc.creator.id | 1014227571 | |
| dc.creator.id | 1030570072 | |
| dc.creator.id | 1032502360 | |
| dc.date.accessioned | 2026-10-10T23:38:06Z | |
| dc.date.issued | 2026-09-21 | |
| dc.description.abstract | La investigación analiza cómo la inteligencia artificial (IA) puede fortalecer la toma de decisiones gerenciales en la gestión del cronograma de proyectos. Ante la alta incertidumbre y complejidad de los entornos actuales, las metodologías tradicionales de planificación y control presentan limitaciones para anticipar desviaciones y gestionar cambios dinámicos. El estudio explora el uso de modelos predictivos, análisis de datos y técnicas de optimización para mejorar el desempeño temporal y reducir la dependencia del juicio subjetivo. Se busca cerrar la brecha entre la teoría de la IA y su aplicación práctica, proporcionando un enfoque analítico para optimizar la precisión en la planificación y la asignación de recursos en la dirección de proyectos. | spa |
| dc.description.abstract | This research analyzes how artificial intelligence (AI) can strengthen managerial decision-making in project schedule management. Given the high uncertainty and complexity of today's environments, traditional planning and control methodologies have limitations in anticipating deviations and managing dynamic changes. The study explores the use of predictive models, data analysis, and optimization techniques to improve time performance and reduce reliance on subjective judgment. It aims to bridge the gap between AI theory and its practical application, providing an analytical approach to optimize the accuracy of planning and resource allocation in project management. | eng |
| dc.description.degreelevel | Especialización | spa |
| dc.description.degreename | Especialista en Gerencia de Proyectos | spa |
| dc.description.tableofcontents | El documento presenta una estructura detallada que incluye: Planteamiento del Problema, Pregunta de Investigación, Objetivos (General y Específicos), Justificación, Marco Teórico, Antecedentes, Diseño metodológico, Resultados y análisis de la información (cuantitativos y cualitativos), Discusión de los hallazgos, Conclusiones y Referencias. | spa |
| dc.format | ||
| dc.format.extent | 51 páginas | |
| dc.format.medium | Recurso electrónico | spa |
| dc.format.mimetype | application/pdf | |
| dc.identifier.instname | instname:Universidad Ean | spa |
| dc.identifier.local | BDM-PGPI | |
| dc.identifier.reponame | reponame:Repositorio Institucional Biblioteca Digital Minerva | spa |
| dc.identifier.repourl | repourl:https://repository.ean.edu.co/ | |
| dc.identifier.uri | https://hdl.handle.net/10882/19651 | |
| dc.language.iso | spa | |
| dc.publisher.faculty | Facultad de Ingeniería | spa |
| dc.publisher.program | Especialización en Gerencia de Proyectos | spa |
| dc.relation.references | Adamantiadou , D. S., & Tsironis, L. (2025). Leveraging artificial intelligence in project management: A systematic review of applications, challenges, and future directions. Computers , 14 (2), 66. https://doi.org/10.3390/computers14020066 | |
| dc.relation.references | Ahmad, M., & Wilkins, S. (2025). Purposive sampling in qualitative research: A framework for the entire journey. Quality & Quantity , 59 , 1461 – 1479. https://doi.org/10.1007/s11135 - 024 - 02022 - 5 | |
| dc.relation.references | American Psychological Association. (2002). Ethical principles of psychologists and code of conduct (Standard 8.02: Informed consent to research). https://www.apa.org/ethics/code | |
| dc.relation.references | Bahroun, Z., Tanash, M., As'ad, R., & Alnajar, M. (2023). Artificial intelligence applications in project scheduling: A systematic review, bibliometric analysis, and prospects for future research. Management Systems in Production Engineering , 31 (2), 144 – 161. https://doi.org/10.2478/mspe - 2023 - 0017 | |
| dc.relation.references | Batool, A., Zowghi, D., & Bano, M. (2025). AI governance: A systematic literature review. AI and Ethics , 5 , 3265 – 3279. https://doi.org/10.1007/s43681 - 024 - 00653 - w | |
| dc.relation.references | Brynjolfsson, E., & McElheran, K. (2016). The rapid adoption of data - driven decision - making. American Economic Review , 106 (5), 133 – 139. https://doi.org/10.1257/aer.p20161016 | |
| dc.relation.references | Chong, H. Y., Yang, X., Goh, C. S., & Luo, Y. (2025). BIM and AI integration for dynamic schedule management: A practical framework and case study. Buildings , 15 (14), 2451. https://doi.org/10.3390/buildings15142451 | |
| dc.relation.references | Council for International Organizations of Medical Sciences . (2016). International ethical guidelines for health - related research involving humans . CIOMS. https://cioms.ch/wp - content/uploads/2017/01/WEB - CIOMS - EthicalGuidelines.pdf | |
| dc.relation.references | Czernek - Marszałek, K., & McCabe, S. (2024). Sampling in qualitative interview research: Criteria, considerations and guidelines for success. Annals of Tourism Research , 104 , 103711. https://doi.org/10.1016/j.annals.2023.103711 | |
| dc.relation.references | Davenport, T. H., & Harris, J. G. (2007). Competing on analytics: The new science of winning . Harvard Business School Press. | |
| dc.relation.references | Elsaid, M., Nassar, K., Alqahtani, F. K., & Abotaleb, I. (2025). Comparative analysis of earned value management techniques in construction projects. Scientific Reports , 15 , 23606. https://doi.org/10.1038/s41598 - 025 - 05834 - z | |
| dc.relation.references | Hashimzai, I. A., & Mohammadi, M. Q. (2024). The integration of artificial intelligence in project management: A systematic literature review of emerging trends and challenges. TIERS Information Technology Journal , 5 (2), 153 – 164. https://doi.org/10.38043/tiers.v5i2.5963 | |
| dc.relation.references | Hernández - Sampieri, R., & Mendoza, C. (2018). Metodología de la investigación . McGraw - Hill Interamericana. | |
| dc.relation.references | Ibadildin, N., Kenzhin, Z., Yeshenkulova, G., Ismailova, R., Nurguzhina, A., Nassanbekova, S., & Kadyrova, A. (2025). Artificial intelligence in project management: A bibliometric analysis. Problems and Perspectives in Management , 23 (2), 252 – 264. https://doi.org/10.21511/ppm.23(2).2025.17 | |
| dc.relation.references | Jayakannan, S. M. (2025). Real - time dynamic scheduling in construction: An artificial intelligence approach. World Journal of Advanced Research and Reviews , 26 (2), 2631 – 2636. https://doi.org/10.30574/wjarr.2025.26.2.1888 | |
| dc.relation.references | Khan, M. F. (2025). Artificial intelligence in project scheduling management: A systematic literature review [Master's thesis, University of Vaasa]. Osuva Institutional Repository. | |
| dc.relation.references | Khajesaeedi, S., Sadjadi, S. J., Barzinpour, F., & Tavakkoli - Moghaddam, R. (2025). Resource constrained project scheduling problem: Review of recent developments. Journal of Project Management , 10 (1), 1 – 26. https://doi.org/10.5267/j.jpm.2024.12.002 | |
| dc.relation.references | Koszykowski, M., & Orzeszko, W. (2025). Machine learning in project schedule creation: A systematic literature review. Journal of Scheduling . https://doi.org/10.1007/s10951 - 025 - 00857 - w | |
| dc.relation.references | Lorenzini, E., Osorio - Galeano, S. P., Schmidt, C. R., & Cañón - Montañez, W. (2024). Practical guide to achieve rigor and data integration in mixed methods research. Investigación y Educación en Enfermería , 42 (3), e02. https://doi.org/10.17533/udea.iee.v42n3e02 | |
| dc.relation.references | Mayo - Alvarez, L., Alvarez - Risco, A., Del - Aguila - Arcentales, S., Sekar, M. C., & Yañez, J. A. (2022). A systematic review of earned value management methods for monitoring and control of project schedule performance: An AHP approach. Sustainability , 14 (22), 15259. https://doi.org/10.3390/su142215259 | |
| dc.relation.references | National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research. (1979). The Belmont Report: Ethical principles and guidelines for the protection of human subjects of research . U.S. Department of Health and Human Services. https://www.hhs.gov/ohrp/sites/default/files/the - belmont - report - 508c_FINAL.pdf | |
| dc.relation.references | Ranganathan, P., Caduff, C., & Frampton, C. M. A. (2024). Designing and validating a research questionnaire — Part 2. Perspectives in Clinical Research , 15 (1), 42 – 45. https://doi.org/10.4103/picr.picr_318_23 | |
| dc.relation.references | Russell, S. J., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson. | |
| dc.relation.references | Sahu, P., Bera, D. K., Parhi , P. K., & Kandpal, M. (2025). Smart delay prediction: Supervised machine learning solutions for construction projects. Journal of Mechanics of Continua and Mathematical Sciences , 20 (6), 154 – 167. https://doi.org/10.26782/jmcms.2025.06.00010 | |
| dc.relation.references | Shinde, R. (2024). Adaptive scheduling: Applying AI and machine learning to optimize project timelines and resources. Journal of Information Systems Engineering and Management , 9 (3). https://www.jisem - journal.com/download/JISEM - Septeber - 2024.pdf | |
| dc.relation.references | Shmueli, G., Bruce, P. C., Gedeck, P., & Patel, N. R. (2020). Data mining for business analytics: Concepts, techniques, and applications in Python . John Wiley & Sons. | |
| dc.rights.accessrights | info:eu-repo/semantics/openAccess | |
| dc.rights.coar | http://purl.org/coar/access_right/c_abf2 | |
| dc.rights.creativecommons | Atribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0) | |
| dc.rights.license | Atribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0) | |
| dc.rights.local | Abierto (Texto Completo) | spa |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-sa/4.0/ | |
| dc.subject.armarc | Administración de proyectos | spa |
| dc.subject.armarc | Control de proyectos | spa |
| dc.subject.armarc | Inteligencia artificial | spa |
| dc.subject.armarc | Negocios -- Toma de decisones | spa |
| dc.subject.armarc | Planificación estratégica | spa |
| dc.subject.armarc | Analítica de negocios | spa |
| dc.subject.mpirdes | Dirección de proyectos | spa |
| dc.subject.proposal | Inteligencia artificial | spa |
| dc.subject.proposal | Gestión de proyectos | spa |
| dc.subject.proposal | Cronograma de proyectos | spa |
| dc.subject.proposal | Toma de decisiones gerenciales | spa |
| dc.subject.proposal | Análisis predictivo | spa |
| dc.subject.proposal | Optimización de tiempos | spa |
| dc.title | La inteligencia artificial como herramienta de apoyo a la toma de decisiones gerenciales en la gestión del cronograma de proyectos | spa |
| dc.title | Artificial intelligence as a tool to support managerial decision-making in project schedule management | eng |
| dc.type | Trabajo de grado - Especialización | spa |
| dc.type.coar | http://purl.org/coar/resource_type/c_7a1f | |
| dc.type.coarversion | http://purl.org/coar/version/c_ab4af688f83e57aa | |
| dc.type.content | Text | |
| dc.type.driver | info:eu-repo/semantics/bachelorThesis | |
| dc.type.other | Trabajo de grado - Especialización | |
| dc.type.redcol | http://purl.org/redcol/resource_type/TP | |
| dc.type.version | info:eu-repo/semantics/acceptedVersion | |
| dspace.entity.type | Publication | |
| person.affiliation.name | Especialización en Gerencia de Proyectos | |
| person.affiliation.name | Especialización en Gerencia de Proyectos | |
| person.affiliation.name | Especialización en Gerencia de Proyectos | |
| person.affiliation.name | Especialización en Gerencia de Proyectos |
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