# Challenges of Engineering Skillsets Essential for Driving Circularity of Smart Cities
## 3 Materials and Methods
### Data
#### 3.1.2 Questionnaire Formulation and Analysis
\begin{table}
\begin{tabular}{c c} \hline
**Question** & **Area *** \\ \hline What is your role relating to a smart city or circular project/practice? & E, CE, SC, and K \\ \hline What are the specific responsibilities of your role? & E \\ \hline Have there been any challenges which you have faced which have hindered your ability to meet & E and SC \\ \hline certain goals during the implementation of smart technologies? & E and SC \\ \hline Have new technologies had an impact on your day-to-day work? If so, what technologies and & E and SC \\ what impacts? & \\ \hline Do you believe that your role could ever fully be rendered obsolete due to the ‘Internet of & SC \\ Things (IoIs)’ or other smart technologies? (Yes/No) & \\ \hline Is there any restriction or enforcement by governmental policy to implement circular practices & E, CE, and SC \\ or economy within the smart city framework? & E, SC, and M \\ \hline How do you involve various stakeholders in your smart city project(s)? & E, SC, and M \\ \hline What do you believe the next steps will be for your business based on emerging circular & CE and M \\ technologies and practices? & \\ \hline Would you like to share any other perspectives on this topic? If deemed relevant to the research & E \\ these may be used as expert opinions in the dissertation and you will be duly credited. & E \\ \hline Have you implemented circular economy/practices in your project(s)? & E and CE \\ \hline In a nutshell, what is the main barrier to the implementation of CE that you have seen & E, CE, and M \\ in your project(s)? & \\ \hline How do you stay updated on the latest developments or updates in the smart technology field & SC and M \\ relevant to your job? & SC, M, and K \\ \hline How are privacy and security concerns due to smart city technologies in your work addressed? & E, SC, M, and K \\ \hline What role do data analytics and insights from smart technologies play in decision-making & \\ processes within your team or organization? & E, SC, M, and K \\ \hline What educational background is needed for your role? & E and K \\ \hline What hard skills are needed? & E and K \\ \hline What soft skills are needed? & E and K \\ \hline Are there opportunities for professional development? & M \\ \hline Are there any employee testimonials I can have access to? & E \\ \hline What skillset is needed to perform your work? Knowledge of any specific disciplines & E and K \\ or programs? & \\ \hline Has the skillset required to perform your job changed since you were first employed? & E and K \\ \hline Is proficiency in another language preferable for your work? & E and M \\ \hline How do you apply the notions of life cycle assessments to the decision-making process in a & E, CE, SC, and K \\ smart city framework? & \\ \hline \end{tabular}  
* skills and experience (E), circular economy (CE), smart cities (SC), mindset indicators (M), and engineering knowledge (K).  
\end{table} 
Table 1: Examples of interview questions designed to gather necessary information and insights from the expert interviews. would indicate that an effect is present (the effect being common transferable skills and capabilities among the industry experts working in the field). This ensures that the results obtained are as repeatable and reliable as possible whilst keeping this study efficient as a sample size that is too large would be inefficient and time-consuming. There are no strict guidelines in research for sample size determination concerning qualitative data. Rather the goal is to achieve a point of data saturation, where the data are repeated to the point where any conclusions are proven without reasonable doubt and further data collection is deemed unnecessary [42]. The most appropriate procedure was to review existing research articles and books concerning the collection and analysis of qualitative data to deduce an appropriate sample size. This is technically a grounded theory study, one that does not have a hypothesis before data are collected; thus, new insights can be derived from data [43; 44].