## 5 Results and Robustness Analysis
### Results
A \"Positive\" sign signifies that the presence or high value of the condition aligns with a high likelihood of the outcome (propensity for failure), while a \"Negative\" sign indicates that the presence or high value of the condition aligns with a low likelihood of the outcome (no propensity for failure). As already mentioned, a key tool in fsQCA is the truth table, which systematically analyzes all possible combinations of conditions and their relationship to the outcome. A condition is considered sufficient if it consistently leads to the outcome, meaning that cases exhibiting that condition also exhibit the outcome [63]. The truth table lists all possible configurations of conditions, with each row representing a unique combination. Cases are assigned to the configuration with the highest membership score (above 0.5). These configurations are then analyzed using Boolean algebra to identify simplified expressions that capture the key causal relationships. This process often involves logical minimization techniques such as the Quine-McCluskey algorithm [58]. With seven conditions in this study, the truth table comprises 128 rows, representing all possible causal configurations (2n rows). Once we have obtained the truth table of all possible causal configurations leading to a high propensity for business failure, the next step is to measure the solutions using consistency and coverage to evaluate their empirical validity. Consistency evaluates the degree to which a causal condition or configuration is consistently associated with the presence of an outcome. Coverage, on the other hand, measures the extent to which that condition or configuration accounts for the occurrence of the outcome across all cases where the outcome is present. Table 5 presents the results of the sufficiency analysis conducted using fsQCA, examining the conditions associated with a high propensity for business failure. The sufficiency analysis aims to identify the combinations of conditions that are sufficient for producing a particular outcome. A condition is considered sufficient if its presence consistently leads to the outcome; in other words, whenever the condition is present, the outcome is also present. This analysis, which included seven potential antecedent conditions, yielded three causal configurations associated with the outcome, derived from the truth table and the logical \begin{table}
\begin{tabular}{c c} \hline \hline
**Condition** & **Expected Sign** \\ \hline SOLL & Negative \\ \hline RTAS & Negative \\ \hline ROA & Negative \\ \hline GEAR & Positive \\ \hline TPR & Negative \\ \hline PPE & Negative \\ \hline TRUCAM & Negative \\ \hline \hline \end{tabular} Notes: The “negative” sign indicates that the condition is expected to contribute to a low score on the outcome (propensity for business failure), and the “positive” sign indicates that the condition is expected to contribute to a high score on the outcome (propensity for business failure). Table 3 contains the definition of the variables.  
\end{table} 
Table 4: Expectations between causal conditions and propensity for failure. minimization process described previously. The overall solution demonstrates reasonable consistency (0.802) and coverage (0.223). Three possible solutions or causal configurations lead to the outcome (a high propensity for business failure):  
1. First solution: Low values of solvency ratio (SOLL) and low values of profit per employee ratio (TPR) and low values of benefit per employee ratio (PPE). 2. Second solution: High values of debt ratio (GEAR), and low values of profit per employee ratio (TPR) and low values of benefit per employee ratio (PPE). 3. Third solution: Low values of economic profitability ratio (RTAS) and low values of profit per employee ratio (TPR) and low values of benefit per employee ratio (PPE) and high values of environmental impact on results (TRUCAM). In this analysis, the symbol \"-\" is used to represent the absence of a specific condition or variable (or low values).