# Enhancing Knowledge on Energy Refurbishment of Buildings and Green Procurement through Living Labs
## 3 Results
### Statistical Relevance of the Results
To summarize, the eGPP area leads the way when it comes to achieving the highest levels of knowledge, particularly on the topics of eGPP, \"green policy\", and \"best practice\". However, each area has its strengths and areas for improvement, reflecting the different focus and outcomes of the LLs' learning initiatives. The results are presented in Table 4.  
To examine how the knowledge was improved after participating in LLs among different _types of organizations_, [PERSON]'s exact test was deployed. A statistical relevant difference in relation to type of organization was found between the level of knowledge on funding topics (\(p=0.017\)) and LL concept (\(p=0.034\)). The results are presented in Table 5.  
The analysis, of which the results are presented in Table 6, highlights that stakeholders from higher education and research organizations have demonstrated a notably high proficiency in understanding the LL concept, with 66.7% achieving an excellent level of knowledge, significantly outperforming other types of organizations. This contrast becomes even more apparent when examining their proficiency in funding topics, where the majority (66.7%) attained very good knowledge. In comparison, SMEs led the chart in reporting excellent knowledge in funding topics, with 27.8% of them achieving these levels. Most stakeholders from public authorities reported their knowledge on funding and LL concepts as good (41.5%/45.3%). On the other hand, business support organizations have shown limitations in reaching the highest level of knowledge in both funding and LL concept topics. Their knowledge spectrum is predominantly bifurcated, with an even \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Topics** & **Pearson Chi-Square** & **Likelihood Ratio** & **Fisher-Freeman–Halton Exact** & \(p\) \\ \hline Green Policies & 25.434 * & 29.772 & 26.261 & 0.001 \\ Mentoring & 29.314 * & 31.264 & 24.845 & 0.004 \\ Funding & 16.929 * & 17.550 & 16.476 & 0.120 \\ Procurement & 28.169 * & 29.791 & 23.586 & 0.005 \\ Best Practices & 34.320 * & 38.953 & 32.326 & \textless{}0.001 \\ LL concept & 19.767 * & 21.756 & 18.656 & 0.042 \\ Pilots & 19.498 * & 19.928 & 18.226 & 0.057 \\ eGPP & 28.895 * & 29.365 & 24.127 & 0.005 \\ \hline \hline \end{tabular}  
* 20 cells (80.0%) have expected count less than 5. The minimum expected count is 0.07.  
\end{table} 
Table 3: Fisher–Freeman–Halton Tests (topics and scope of LLs). in LLs leads to a consistent improvement in knowledge levels. We observed a more pronounced enhancement in knowledge levels after participating in an LL for topics such as understanding the Living Lab (LL) concept, best practices, green policies, pilot actions, and funding. The increase in level of knowledge in other topics was only slightly less pronounced. Although, in general, across all these categories, there has been a positive change in ratings, moving from the 'Fair' range closer to or into the 'Good' range, with some topics even reaching the 'Excellent' category. This suggests that participating in an LL had enhanced the level of knowledge in energy refurbishment and green procurement. The potential reasons for this may lie in the collaborative learning environment. LLs typically foster a collaborative environment where participants can learn from each other. This exchange of ideas and experiences can enhance the learning process, leading to better retention and understanding of concepts. Also, in the case of LLs, learning regarding the energy refurbishment of buildings is put in the context of real-world applications (through pilot actions) that can make abstract concepts more tangible and easier to grasp. LLs often involve experts in the field who provide guidance, insights, and feedback to participants. Learning about energy from financial experts can significantly boost the understanding on carrying out energy refurbishment of buildings and green public procurement.