Statistical Predictors of Project Management Maturity - Celani de Souza, Helder Jose [UNESP]; Salomon, Valerio Antonio Pamplona [UNESP]; Sanches da Silva, Carlos Eduardo (MDPI, 2023)
Global scenarios of organizations show investments wasted in projects with poor performances in more than 11 percent of cases, according to the Project Management Institute. This research aims to guide organizations in assertively investing in the right pertinent factors to improve project success rates and speed up project management maturity at a higher accuracy level using statistical predictions. Challenging existing drivers for project management maturity models and expanding their current practical view will be the result of a quantitative methodology based on a survey supported by data collection targeting the project management community in Brazil. The originality and value of this research are in contributing to the development of new project maturity models statistically supported by the increasing rate of maturity accuracy, which can be continually improved by confident data input into the model. The results show a high correlation between the performance measurement system and the project success rate associated with project management maturity. In addition, this research contemplates the relationship between organizational culture, business type, and project management office and project management maturity.
Keywords: partial least squares regression; performance measurement; project management