## 3 Materials and Methods
### Research Methodology
#### 3.3.1 Case Study Selection and Data Collection  
A real Italian automotive company was selected as the case study to investigate the potential of the proposed approach. The automotive sector has been selected as it is one of the most important economic sectors globally [41] and has recently experienced a paradigm shift led by new technologies. Furthermore, the literature review identified a lack of empirical studies in this sector. Similarly, the company was selected due to its relevance and the complexity of its supply chain. Indeed, with almost 500 million in revenues, the industry relies on more than 600 suppliers who supply, on average, 10,000 components.  
Two different types of data were collected from the selected case study. First, suppliers' delivery performance data for 134 different components, supplied from 24 suppliers, were recorded from 2021-2022. Specifically, data were restricted to those deliveries for which at least 30 delivery data points had been recorded. It was decided to restrict the amount of data to components for which at least 30 deliveries had been recorded to guarantee a minimum amount of data for training and testing the proposed approach properly. Similar methodological strategies were applied by [16]. Second, multiple macroeconomic variables that are considered to affect suppliers' potential deliveries were identified based on the expertise of the company's SC manager. The Eurostat database was chosen as a data source due to its reliability and wide coverage of European company data. An overview of the collected data is reported in Table 2, while summary statistics of the delivery performance data are reported in Table 3.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Information** & **Value/Source** \\ \hline Company sector & Automotive \\ Company collected data & Historical days of delay or advance in the delivery of a specific component \\ Data collection period & January 2021–December 2022 \\ Considered suppliers & 24 \\ Considered components & 134 \\ Macroeconomic data source & EUROSTAT \\  & 1. Inflation rate of each European country \\  & 2. Producer prices in the industry of different economic activities in the \\  & European Union for each European country \\ Macroeconomic collected variables & 3. Production in the industry index of different economic activities in the \\  & European Union for each European country \\  & 4. Production in the service index of different economic activities in the \\  & European Union for each European country \\ \hline \hline \end{tabular}
\end{table}
Table 2: Case study data collection.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Supplier** & \begin{tabular}{c} **Number of** \\ **Components** \\ \end{tabular} & \begin{tabular}{c} **Minimum** \\ **Value** \\ \end{tabular} & \begin{tabular}{c} **Mean** \\ **Value** \\ \end{tabular} & \
\begin{tabular}{c} **Standard** \\ **Deviation** \\ \end{tabular} &
\begin{tabular}{c} **Maximum** \\ **Value** \\ \end{tabular} \\ \hline
1 & 9 & \(-63\) & 0.7 & 10.8 & 47 \\
2 & 1 & 6 & 30.7 & 12.8 & 62 \\
3 & 1 & \(-4\) & 24.2 & 19.3 & 57 \\
4 & 2 & \(-7\) & 11.2 & 9.0 & 40 \\
5 & 1 & \(-9\) & 20.9 & 11.5 & 50 \\
6 & 1 & \(-22\) & 8.5 & 13.7 & 61 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Summary statistics of supplier delivery performance data.