## 5 Conclusions
With regard to cost forecasts, the CTCR methodology is based on the metrics proposed by EVM owing to their efficiency, which has been proven and presented in the previous research carried out by the authors and has already been cited previously in this work, where the behavior of the probability of fit can be appreciated in the same case studies presented in the present work. The verification and demonstration of the efficiency of the application of the CTCR methodology in the four case studies is supported by statistical analyses, where probabilistic analyses and Monte Carlo simulation were initially applied to check efficiency in predicting the durations or periods of the project between the CTCR and EVM methods. We conclude that in the four case studies, the CTCR method demonstrates that it is more efficient than EVM in all of the simulations of execution of the projects. This is summarized in Figures 2-5. In addition, an ANOVA analysis or analysis or variance was performed to test the efficiency of period predictions through hypothesis testing, which determines whether the means of the prediction periods in different periods are equal to the value of the mean period from the simulation. From the results obtained and presented in Tables 4-7, we conclude that the CTCR method makes more efficient predictions than EVM, giving reliable predictive values with sufficient time for decision making prior to the completion of the project. In countries such as Ecuador, where the government plans the construction of new hydroelectric plants in the short term, it is essential to have new control and monitoring methodologies that are able to improve the bad historical indicators of cost and execution time obtained from this kind of project. On the contrary, the results obtained in this work show the potential of the methodology to increase efficiency in the management and control of these projects but also in any other type of complex construction project. The proposed methodology simultaneously considers four fundamental parameters for project management, which provides greater efficiency compared to other traditional techniques. This work makes it possible to appreciate this potential through the application to four real case studies within the hydropower sector. In addition, the application of multicriteria decision techniques, specifically the Analytic Hierarchy Process, to manage the impact of some parameters during the analyses of the project development represents another aspect of great interest for further works. In this way, the authors identify two main research lines for further works in this field. First, there is the exploration of the possibilities of multicriteria techniques in the development of methodologies for the control and monitoring of complex projects. Second, the application of methodological approaches, as the one presented in this work, in projects in other sectors is another promising research area. Conceptualization, P.U., J.C. and M.A.S. ; methodology, P.U., J.C. and M.A.S. ; validation, P.U., J.C. and M.A.S. ; formal analysis, P.U., J.C. and M.A.S. ; investigation, P.U., J.C. and M.A.S. ; resources, J.C. and M.A.S. ; data curation, J.C. and M.A.S. ; writing--original draft preparation, P.U., J.C. and M.A.S. ; writing--review and editing, P.U., J.C. and M.A.S. ; visualization, P.U. and J.C.; supervision, M.A.S. ; project administration, J.C. and M.A.S. ; funding acquisition, J.C. and M.A.S. All authors have read and agreed to the published version of the manuscript. This research was funded by International School of Doctorate of the National University of Distance Education (UNED) with resources from the Postgraduate and Professional Development Program entitled Administration, Planning and Project Management (Administracion, Planificacion y Direccion de Proyectos), which is taught at the UNED and in which the authors collaborate.