# Citizens' Perception of Smart Cities: A Case Study
## 4 Survey Methodology and Analysis
### Analysis
#### 4.3.2 Research Questions Analysis--Second Category  
In this section, we present the responses from participants that declared themselves as non-familiar with the smart city term. An amount of 226 (41.5% of the total participants) were declared as non-familiar with the smart city term.  
At the beginning, the participants were asked if they are willing to learn more things about the smart city concept in the future so that they can understand the term better. A vast amount of them (89.8%) answered \"Yes\".  
Then the participants were asked about whether the local authorities in their city have taken initiatives to inform them about the Smart City concept or not. The results have shown that over half of the respondents claimed that they don't think that this kind of initiative has been taken in their city, by answering \"No\" (50.4%). The 43.4% of the participants showed unawareness on the subject while only 6.2% (which corresponds to only 14 out of 226 respondents) answered \"Yes\".  
Subsequently, the \"non-familiar\" participants were asked whether they would be willing to participate in the decision-making for the development of their city via a digital platform or not. The vast majority of them (71.2%) answered \"Yes\", while 27.4% did not appear to be sure. Only 1.4% showed no interest in taking part in decisions for projects related to their city.  
Afterwards, to investigate if the education level factor determines the way that the number of non-familiar participants is formed we run the Chi-square test and we noticed that 33.3% of the cells have expected count less than 5. In this case, we check the \"Fisher-Freeman-Halton\" \(p\)-value. Since it is lower than 0.05 (\(p\)-value \(<\) 0.001), the result is statistically significant, and the independence hypothesis is rejected. In other words, there is a dependency between the variables and this means that education is indeed related to the fact that a participant is or is not familiar with the term.  
Based on Figure 8, it is clearly concluded that most of those who have a lower educational level (secondary education and below) tend to be non-familiar with the smart city term, whereas most of those who have a high educational level (\"Higher education\" and above) tend to be more familiar with it, by even just having heard of it.  
The next hypothesis' question is the following: Is age a determinant factor regarding the participants' interest for further learning about \"Smart Cities\" in the future?  
Figure 7: Challenges based on participant’s belief.  
We notice that 40% of the cells have an expected count less than 5. In this case, we check the \"Fisher-Freeman-Halton\"-value. Since 0.562 \(>\) 0.05, the independence hypothesis cannot be rejected. In other words, the variables are not likely to be associated, thus age is not a determinant factor regarding the participants' interest for further learning about \"Smart Cities\" in the future.  
The final hypothesis' question is: Is the city a determinant factor regarding the participants' interest for further learning about \"Smart Cities\" in the future?  
We notice that 33.3% of the cells have an expected count of less than 5. In this case, we check the \"Fisher-Freeman-Halton\" \(p\)-value. Since 0.779 \(>\) 0.05, the independence hypothesis cannot be rejected. In other words, the variables are not likely to be associated, thus the city is not a determinant factor regarding the participants' interest for further learning about \"Smart Cities\" in the future. To sum up, the results have shown that most of the participants are interested in learning new things reagrds to the smart city concept in the future, regardless of their age and the city in which they live.