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Publicación Model for the Creation and Decision-Making in Project Management Offices (PMO)(Springer Nature, 2025-03-25) Fuentes-Ruiz, Daniel Alejandro; Alvarado-Acuña, Luis Segundo; Heredia-Rojas, Boris Fabrizio; Huidobro-Arabia, Juan Elías; Piñero-Pérez, Pedro-Yobanis; Yzquierdo-Herrera, RaykenlerDuring the evolution of project management, various authors have proposed theories regarding the roles and structures of Project Management Offices (PMOs). In literature, a wide variety of PMOs can be identified. Each PMO has essentially been tailored to the organization that supports it. However, the high rate of project and PMO failures suggests that it is possible to generalize the best practices. The first section of the methods chapter introduces various concepts related to project management and PMOs. The second section presents a model for the creation and decision-making processes within PMOs. The core of the proposal focuses on decision-making methods for PMOs and how these methods evolve with the introduction of artificial intelligence. Additionally, different PMO contexts and best practices for the scenarios analyzed are discussed. The study also examines various roles within PMOs and their relationship to project management maturity levels. In the results analysis, the proposal is validated by subject matter experts using computational techniques based on linguistic approximations and the Delphi method.Publicación Platform for Project Management IADESPro, Supported by Artificial Intelligence(Springer Nature, 2025-03-25) Álvarez-Sago, Yunieck; Piñero-Pérez, Pedro Yobanis; Pérez-Pupo, Iliana; Yzquierdo-Herrera, Raykenler; Alvarado-Acuña, Luis Segundo; Hernández-Pupo, Luis GabrielThis work addresses the challenges of managing science and innovation projects, with a particular focus on the issues faced by the international science and innovation funding and project management office of CITMA. As part of the study, a state-of-the-art review is conducted to examine trends in project management. A critical analysis based on the literature is then presented. In the methods section, a proposed platform for project management, called IADESPro, is introduced. The proposed platform is based on agile management methods and performance domains, incorporating best practices from PMBOK and ISO standards. The platform is supported by artificial intelligence techniques to aid decision-making. The proposed platform focuses on value generation, covering the various performance domains of project management. In the results section, the implementation of the platform is evaluated in the context of managing research and innovation projects. A comparison is made between the proposed platform and others reported in the literature, with a critical analysis of their advantages and disadvantages. The feasibility of the proposal is demonstrated, along with its potential for decision-making in environments characterized by uncertainty.