## 4 Results
In the case of specific goals, such as GOAL 1: No Poverty, GOAL 2: Zero Hunger, and GOAL 5: Gender Equality, the mediation is not statistically significant, suggesting that GDP per capita does not play a mediating role in these relationships. Thus, while H1 is confirmed for models \(\alpha\) and 1-5, H2 requires a more nuanced interpretation, considering the variations depending on the specific SDG goal and the direction of the economic mediation. Figure 3 presents models 6-11 illustrating the DESI components' direct and indirect influences on the indices associated with SDG goals 6-11. DESI components have a reflexive relationship with the latent variable [73]. Other latent variables, such as Economic performance, GOAL 6: Clean Water and Sanitation, GOAL 7: Affordable and Clean Energy, GOAL 8: Decent Work and Economic Growth, GOAL 9: Industry, Innovation and Infrastructure, GOAL 10: Reduced Inequality, GOAL 11: Sustainable Cities and Communities, each have an observable variable (GDP per capita and indices for SDG goals 6-11). The outer loadings of exogenous variables (observables) in the six models are above 0.7, further increasing the model's significance. Furthermore, [PERSON]'s alpha values (0.909), composite reliability (0.942), and average variance extracted (0.844) for the Digital Economy and Society Index latent variable are high for all six models. Table A2 (see Appendix A) presents the discriminant matrices for the six models and the SRMR. Through bootstrapping with a significance level of 0.05 and conducting two-tailed tests, we determined the direct and indirect effects from models 6-11 (Table A5 in Appendix B). Analyzing the data from the six models reveals a significant positive impact of emerging technologies measured through the DESI on SDG progress in European Union countries, which suggests that hypothesis H1 is supported. This issue is evident from the statistically significant coefficients between the DESI and various sustainable development goals (SDG6-SGG11), all with \(p\)-values below 0.05. The results are mixed regarding hypothesis H2, which proposes that economic performance, measured by GDP per capita, positively mediates the relationship between emerging digital technologies and SDG progress. While there are statistically significant mediations for some goals (e.g., GOAL 8, GOAL 9, and GOAL 11), mediation is insignificant or negative in other cases. For example, in model 7, the indirect effect of DESI on GOAL 7 through economic performance is negative and significant (coefficient \(-\)0.338, T value 6.469, \(p\) value 0), suggesting a potentially adverse mediating effect of GDP per capita in this context. In conclusion, hypothesis H1 is supported across models 6-11, indicating that emerging digital technologies positively impact SDG progress. However, hypothesis H2 yields mixed results, indicating that the mediating role of economic performance varies depend  
Figure 3: Models for the direct and indirect influence of the DESI on SDG6–SDG11. Source: authors’ design using SmartPLS v3.0. ing on the specific sustainable development goal and may have both positive and negative effects. Unsustainable economic growth may negatively affect some SDGs. Figure 4 describes models 12-17, illustrating the DESI components' direct and indirect influences on the indices associated with SDG12-SDG17. The DESI components exhibit a reflexive relationship with the latent variable. The other latent variables--Economic Performance, GOAL 12: Responsible Consumption and Production, GOAL 13: Climate Action, GOAL 14: Life Below Water, GOAL 15: Life on Land, GOAL 16: Peace and Justice Strong Institutions, GOAL 17: Partnerships to achieve the Goal--each have an observable variable (GDP per capita and the indices for the SDG12-SDG17 goals). The outer loadings of the exogenous (observable) variables in the six models are above 0.7, enhancing the model's significance.