## 2 Research Method
### Consequence Analysis of the Schedule Deficiencies
This work provided a set of 22 causes of scheduling deficiencies, which were derived from a systematic literature review and expert consultation. Second, a preliminary interview instrument was created to explore how these causes manifest in road intersection projects. This instrument was pilot-tested with a group of five professionals to verify the clarity and relevance of the questions and to adjust their format and language as necessary. Third, a final version of the semi-structured interview was developed and conducted with a group of ten experts who have extensive experience in road infrastructure planning. Their responses were used to associate each deficiency with one or more of the five proposed scheduling stages. Finally, the collected data were organized and processed in Microsoft Excel. Each deficiency was recorded for each project as a binary variable (1 = present; 0 = absent) and was further integrated into the Qualitative Comparative Analysis (QCA) using fsQCA 4.1 software. This integration helped identify causal configurations that contribute to schedule and cost deviations. Based on the data collected during the review of project documentation, a Qualitative Comparative Analysis (QCA) was conducted to identify the combinations of causes leading to schedule and budget deviations in road intersection construction projects. QCA is a technique for systematically analyzing qualitative and quantitative data, combining Boolean logic and set theory aspects with traditional comparative analysis. This method allows researchers to identify patterns and causal relationships between variables in studies with a moderate number of cases. The binary nature of the data collected justifies using the QCA method in this research. In addition, QCA is particularly suitable for studies with moderate sample sizes, where it is essential to understand complex causal configurations and interactions between multiple variables. The QCA began with data preparation, creating a dichotomous table in Microsoft Excel (see Figure 3). Columns included the causes of deficiencies, while rows listed the projects. Each project was marked with a \"1\" if it was affected by a particular cause and a \"0\" if not. Two additional columns were created: one for schedule deviation and another for budget deviation. These columns recorded \"1\" if the project experienced a deviation and \"0\" if it did not. This table was then exported to the fsQCA software [44; 45]. Given that the analyzed data were organized dichotomously, Crisp-Set QCA was used. The output variables were the schedule and budget deviations, while the causal conditions were the causes of deficiencies in the schedule planning of the analyzed projects. A truth table was constructed using the input data to verify the different configurations of cause combinations that could lead to deviations. The QCA was conducted in two stages: one focused on schedule deviations and the other on budget deviations. Additionally, the analysis considered the five stages proposed in stage two, assigning the causes of scheduling deficiencies to each stage as determined by an expert workshop. From the identified configurations in the truth table, coverage and consistency for each configuration were calculated. The number of configurations was determined by the number of grouped causes of deficiency in each analyzed stage \(n\), using the expression \(2^{n}\). Coverage (\(CG\)) indicates the proportion of cases where the condition and the outcome of interest appear among the cases showing the condition (see Equation (3)). Consistency (\(CS\)) indicates the proportion of cases with both the condition and the outcome of interest among the total cases showing the outcome of interest [46] (see Equation (4)).