## 4 Application and Results  
In this study, based on the indicator data collected for the 21 European countries for both 2008 and 2015, the hierarchical clustering analysis is first utilized to identify country groups, and the principal component analysis is then applied for each group to calculate the weights of the selected SPIs and to obtain a safety performance index score for each country. In this section, the results on country grouping, index ranking, and weight allocation are presented and further compared between these two years.  
It is interesting to notice that the results on country grouping from Figures 1 and 2 show that the members in each cluster do not change over time. One group contains 13 countries (i.e., Austria, Belgium, Denmark, Finland, France, Germany, Ireland, Italy, The Netherlands, Spain, Sweden, Switzerland, and the United Kingdom), and the other contains the remaining eight countries (i.e., Czech Republic, Estonia, Hungary, Lithuania, Poland, Portugal, Romania, and Slovakia), for both 2008 and 2015.  
The consistency of country grouping in these two years based on the same clustering approach facilitates our group-based country comparison. A colored international map of these 21 European countries is shown in Figure 3, which indicates the geographical distribution of these countries in relation to their background characteristics. It can be seen that most of the western and northern European countries (except Portugal) belong to Group 1, while most eastern European countries are within Group 2.  
To further explore the differences between these two country groups, we calculate the average values of these four background indicators related to different country groups and different years and perform a \(t\)-test to measure the level of their differences. The results are shown in Table 3.  
We can see that for both 2008 and 2015, the average value of each of the four background indicators of country Group 1 is statistically significantly larger than that of country Group 2 (with the \(p\)-value less than 0.05). Hence, from the view of motorization level, economic development, population density, and urbanization level, the countries in Group 1 are more developed than those in Group 2. Thus, country Group 1 can be treated as \"Highly Developed Countries\" and country Group 2 as \"Less Developed Countries\".  
Figure 3: Geographical distribution of the final classifications of 21 European countries related to their background characteristics.  
Moreover, the development trend with respect to these four aspects was different for the two country groups between 2008 and 2015. As for Group 1, all indicators' average values increased to a certain extent during these seven years. However, the situation was completely different for country Group 2. Except for _N_p_cars_, whose average value increased significantly from 369 passenger cars per 1000 inhabitants in 2008 to 424 in 2015, the other three indicators' average values basically did not change (e.g., _Pop_den_ and _Pop_urb_), or even decreased dramatically (e.g., the GDP per head dropped from 66 to 46) from 2008 to 2015. This implies that apart from the motorization level, the overall socioeconomic development gap between these two country groups enlarged during these seven years. Such a result can also be verified by the changing direction of the _p_-values from the _t_-test in Table 3.