Analysis of Organizational Factors and Performance in BIM Projects: Empirical Evidence from the Latin American Construction Industry

Efficient management of construction projects using BIM (Building Information Modeling) technology is essential for optimizing resources, reducing delays, and improving quality in the AEC industry. This study analyzed associations between organizational variables (work area, BIM software used, type of company, level of experience) and key performance indicators (delays, costs, satisfaction) based on a sample of 101 Latin American professionals. Both descriptive techniques and inferential tests (contingency tables, Chi-square, normality tests, Wilcoxon, ANOVA) were applied, depending on the nature of the variables. The main results showed that only the relationship between type of company and level of experience was statistically significant, with independent companies having less BIM experience than consultants and clients (Succar et al., 2022). No significant associations were found between functional area or software used and the frequency of delays or professional satisfaction, consistent with studies that identify management and training factors as key determinants (Eastman et al., 2018; Gu & London, 2010). The quantitative variables showed non-normal distributions, with strong asymmetries and the presence of outliers, reinforcing the need for non-parametric methods and a focus on problematic projects. In addition, it was found that lower levels of experience are associated with greater delays, underscoring the value of continuous training (Barbosa et al., 2017). The study argues that digital maturity and organizational experience are the most relevant factors for success in BIM projects, suggesting that training policies and programs should focus on less experienced actors and reinforce the use of robust statistics for performance monitoring in the construction industry (Chong et al., 2017; Martínez-Rojas et al., 2016).