# Decoding Urban Intelligence: Clustering and Feature Importance in Smart Cities
## 1 Introduction
The outputted ranking highlights the relationship between investments in ICT and a city's ecological, economic, and social progress, meaning that cities with above-average investments in ICT infrastructure typically excel in areas such as infrastructure, environmental protection, public safety, and healthcare. Kearney's Global Cities Report (www.kearney.com/service/global-business-policy-council/gcr accessed on 1 September 2024) ranks the world's cities, rating the rate of attraction, retainment, and generation of global flows of capital, people, and ideas in cities. Two quantitative measures are available: the Global Cities Index (GCI) for measuring the current performance and the Global Cities Outlook (GCO) for performance forecasts. GCI assesses a total of 29 metrics divided into five categories. On the other hand, GCO assesses 13 indicators divided into four categories. Each category weighs the final score of a city. For GCI, business activity and human capital are the factors that contribute the most to smartness. GCO, instead, gives the same importance to the considered factors. The IMD Smart City Index (SCI, www.imd.org/smart-city-observatory/home/ accessed on 1 September 2024) relies on individuals' opinions collected through surveys. The perceptions of 120 residents for each city are assessed by the availability of infrastructure and technological services. Both are judged concerning five dimensions: (i) health and safety, (ii) mobility, (iii) activities, (iv) opportunities, and (v) governance. Weights of the five areas are not predetermined: respondents are asked to select five city priorities from 15 indicators. The weight of each category in the final calculation is adjusted based on the number of selected indicators that fall within that category. Thus, no indicator is thought to be the most influential on smartness in overall assessments. The final score for each city is calculated using weighted data from the past three years: the most recent year's weight is 3 and the least recent year's weight is 1. IESE rates cities via its Cities in Motion Index (CIMI, www.iese.edu/insight/articles/smart-sustainable-cities-in-motion/ accessed on 1 September 2024), yearly adding new indicators of cities health such as the number of private startups worth more than 1 billion dollars or corporations listed in the Fortune Global 500. The index considers 114 indicators, divided into 9 categories: (i) human capital, (ii) social cohesion, (iii) economy, (iv) governance, (v) environment, (vi) mobility and transportation, (vii) urban planning, (viii) international profile, and (ix) technology. Each of the categories has a relative weight, as reported in Table 1. CIMI assigns the highest level of importance to the economy as a factor as a smartness indicator. \begin{table}
\begin{tabular}{l c c} \hline \hline
**Indicator** & **Category** & **Weight** \\  & & **(If Available)** \\ \hline GCI & Business activity & 30\% \\  & Human capital & 30\% \\  & Information exchange & 15\% \\  & Cultural experience & 15\% \\  & Political engagement & 10\% \\ GCO & Personal well-being & 25\% \\  & Economics & 25\% \\  & Innovation & 25\% \\  & Governance & 25\% \\ SCI & Health and safety & variable \\  & Mobility & variable \\  & Activities & variable \\  & Opportunity & variable \\  & Governance & variable \\ CIMI & Human capital & 0.508 \\  & Social cohesion & 0.538 \\  & Economy & 1.000 \\  & Governance & 0.726 \\  & Environment & 0.333 \\  & Mobility and transportation & 0.508 \\  & Urban planning & 0.430 \\  & International profile & 0.533 \\  & Technology & 0.646 \\ SCSI & Budget & 7.50\% \\  & Buildings & 8.33\% \\  & Energy and Environment & 8.33\% \\  & Mobility & 8.33\% \\  & Education & 8.33\% \\  & Health & 8.33\% \\  & Government & 8.33\% \\  & Infrastructure & 10.00\% \\  & Policy and Legal Framework & 10.00\% \\  & Stakeholders & 7.50\% \\  & Coordination & 7.50\% \\  & Plan & 7.50\% \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Categories and weights for the computation of the main smart city indexes.