Methodology

Employing an evidence-based methodology, CitiIQ has created a comprehensive, objective measurement of a city. 

 
 
 
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CitiIQ Hierarchy and Algorithm

 
 

To provide a sufficiently comprehensive and holistic diagnosis, CitiIQ has established an innovative approach to organizing the breadth of Considerations that contribute to the wellbeing of a city in their natural order of priority. 

The result is a scoring system with 35 Considerations, within 5 Dimensions, using data driven by over 120 Indicators. The algorithm normalizes scores out of 100 and weights the scores through non-linear aggregation in order to provide a meaningful, comparative view.

The CitiIQ framework is founded on a thorough analysis of local data, providing unprecedented insight into the ecologies of cities. Through examination of available Indicators and their relationships, a strong foundation for an evidence-based methodology was formed. 

 
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Dimensions

 
 

The Considerations are organized in a hierarchical pyramid inspired by Abraham Maslow’s theory of human motivation. The established hierarchical levels of the CitiIQ framework are: 

  • Basic Needs
  • Competitiveness
  • Opportunity
  • Livability
  • Destiny

The framework demonstrates the priority of community needs such that the most basic needs form the base of the pyramid, indicating that these are forerunners of more advanced aspects. A holistically developing community will aim to advance upwards through the hierarchy. While all Considerations are important, some must be met before others can be prioritized. For example, hope for a future is essential to human well-being; however human life simply cannot sustain without the basic provisions of water, food, and physical safety. The algorithm reflects this reality as scores in the higher Dimensions gain importance with stronger scores in the lower (primary) Dimensions.

 

 
 
 

Considerations

Thirty-five Considerations were identified to be essential building blocks of community health and wellbeing. These were drawn from academic knowledge, internationally recognized institutions, and anecdotal knowledge from professionals working in community development. Each Consideration was assigned to its respective level within the hierarchy, such that a city’s performance in any one Dimension is defined by its performance in all Considerations comprising that Dimension. The Considerations within each Dimension are as follows:

 

Basic Needs

 
 
 

Competitiveness

 
 
 

Opportunity

 
 
 

Livability

 
 
 

Destiny

 
 
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Indicators

 
 

Over one hundred and twenty Indicators form the foundation of the Diagnostic Tool. They are based on quantifiable aspects of a city, generally accessible through publicly available data, and processed through the CitiIQ algorithm.

The list of Indicators (shown below in source data) was developed to optimize comprehensiveness, credibility, accuracy, and likelihood of accessible data. Indicators inform the 35 Considerations to varying degrees, and may inform multiple Considerations in the hierarchy.

The network-like framework of the algorithm reflects its complexity, as well as the interrelated nature of a city’s wellbeing. 

 

 
 
 

Weighting the Data

 
 

In order to make disparate raw data comparable and most useful, it is relativized through a system of normalization and non-linear aggregation. These procedures are explained below.

 

Score Normalization

Since the range of Indicators are measured in diverse ways, the algorithm required a method of normalization such that each Indicator could be scored on a common scale. 

For example, ‘Unemployment’ is generally measured as a percentage of eligible individuals who lack employment; thus, a lower percentage is desirable. By contrast, ‘Life Expectancy’ is typically measured in years, where a higher score is desirable. Thus, normalizing Indicator scores involves mathematically translating these raw values onto a 0-100 scale, where 0 is the worst possible value and 100 is the best.

 

Constraint of Linear Aggregation

Forms of linear aggregation allot equal weight to each part comprising the whole (such as the average or mean); thereby failing to reflect the complex relationships between Indicators and Considerations. For example, while a high score should be an indication of effective performance, aggregating scores linearly (where each is weighted equally) can obscure outlier scores, such as particularly well or poorly scoring Indicators.

To promote clarity and accuracy in exploring community performance of the 35 Considerations, CitiIQ employs non-linear aggregation to combine Indicator scores and to accurately highlight the “gaps” which may otherwise be overlooked.

 

 
 
 
 

The following figure illustrates the bias linear aggregation can introduce into a model. The linear score is calculated by averaging the four scores and the non-linear score is calculated on a weighted basis. 

 
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Normalization Formula

One of four different approaches may be taken to normalize an Indicator depending upon its characteristic as follows:

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Linear

Used when there are defined maximum and minimum values that the Indicator can take. The raw value is scaled proportionally between these values, as shown in the graph. 

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Exponential

Used when there is a precise minimum value the Indicator can take, but no defined maximum amount. As shown in the graph, when the raw value of the Indicator is small, the scaled value increases rapidly, but as the raw value becomes larger and larger, the scaled value gets closer and closer to 100.

 
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Sigmoid

Used when the maximum and minimum values of the Indicator are not defined. The graph tends towards 0 for small raw values, and towards 100 for large raw values, but most of the change occurs within a smaller range of values. 

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Bell Curve

Sometimes there is an ‘ideal’ value for an Indicator, and anything larger or smaller is not as good. In this case, the bell-curve graph is appropriate, where the shape is determined by the standard distribution parameters, the mean and the standard deviation.

 

Non-Linear Aggregation

 
 

The CitiIQ algorithm employs several forms of non-linear aggregation.

Firstly, an Indicator will most likely influence more than one Consideration; however, may not influence each Consideration to the same degree.  For example, the Indicator ‘Greenhouse Gas Emissions’ informs the 3 Considerations “Energy Supply”, “Resilience” and “Green Space”. As the following diagram indicates, this Indicator carries a different weight for each Consideration, reflecting the known strength of its relationship to each Consideration.

Secondly, in the same way the top of a pyramid is only as secure as it’s lower layers, so a city’s measure of wellbeing depends firstly on the primary Dimensions. A community may have a high score for “Signature + Identity”, but if the scores for “Water Supply”, “Food Security” or “Shelter + Housing” are low it does not have a high measure of wellbeing. As a result, only when the primary Dimensions of wellbeing are satisfied, do the other Dimensions factor meaningfully into the score.

The CitiIQ algorithm presents a more accurate critique of the priorities necessary to improve a community’s wellbeing.

 
 
 

The following visualization demonstrates an example of how the 35 Considerations, the 5 Dimensions and the City as a whole might be scored for a particular community:

The following figure illustrates the total CitiIQ score.

 
 
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Data Sources

The key data sources are derived from over 120 Indicators deemed to have the most pertinent effect on the health and wellbeing of a city.

  • Ability to Host Globally Recognised Sporting Events
  • Access to Education
  • Air Quality
  • Annual Growth Rate of GDP
  • Annual Overnight Tourist Numbers
  • Asset Distribution
  • Availability of Nursing & Midwifery Personnel
  • Average Commute Time
  • Average Length of Electrical Interruptions
  • Average Life Expectancy
  • Average Number of Electrical Interruptions
  • Award Winning Buildings
  • Basic City Internet Connection
  • Bedroom Overcrowding
  • Business Start-Up Time
  • Capability of Municipal High
  • Capacity Public Transport
  • Capability of Municipal Light Passenger Public Transport
  • Cause of Death by Infectious or Preventable
  • Conditions Cause of Death by Non-Communicable Disease
  • Censorship Child Mortality
  • City Cycleway Infrastructure
  • City Entertainment Reputation
  • City Green Space
  • City Homicide Rate
  • City Recycling Services
  • City Sporting and Event Facilities
  • City Transportation Fatalities
  • City Tree Canopy
  • City Universities Ranking
  • Cost of Living Credit Rating
  • Cross-Consideration Distinction
  • Current Account Balance
  • Debt Service Ratio
  • Distinction of City Transportation
  • Distinction of Innovation
  • Distinction of Municipal Architecture
  • Drug Related Death Rate
  • Electric Vehicle Market Share
  • Female Voter Participation
  • Food Insecurity
  • GDP Growth Rate per Employed Person
  • GINI Index
  • Greenhouse Gas Emissions
  • Gross Domestic Production Distribution
  • Heritage and Historic City Buildings
  • High Quality City Internet Connection
  • Homelessness Rate
  • Hospital Capacity
  • Housing Affordability
  • ICT Service Exports
  • Incidence of Municipal Malnutrition in Children
  • Income Tax Rate
  • Inequality Index
  • International Attraction
  • International Recognition
  • International Trade Levels
  • Literacy Rate
  • Location of National Government
  • Long-Term Unemployment Rate
  • Median Household Income
  • Median National Income
  • Medicially Qualified Personnel
  • Mercer Liveability Scale
  • Mobile Phone Usage Rate
  • Mother's Mean Age at First Birth
  • Municipal 4G Penetration
  • Municipal Child Labour Rate
  • Municipal Energy Derived from Renewable Resources
  • Municipal Foreign Direct Investment
  • Municipal Gender Inequality
  • Municipal Government Support for Research and Development (R&D tax credit)
  • Municipal Openness to International Business
  • Municipal Population Density
  • Municipal Postgraduate Qualifications
  • Municipal Poverty Rate
  • Municipal Refuse Collection Services
  • Municipal Tourism Revenue
  • National Gender Inequality
  • National Level of Corruption
  • National Population Happiness
  • New Business Density
  • Number of Firefighters
  • Number of Fortune 500 Companies
  • Number of New Patents Issued
  • Number of Police Officers
  • Number of Public Art Galleries
  • Number of Tertiary Degrees
  • Obesity Rate
  • Overall Incidence of Rape
  • Percentage of City Population Living in Slums
  • Percentage of Population with Access to Electricity
  • Popularity of City Restaurants
  • Population Dependency Ratio
  • Population Fertility Rate
  • Population Savings Rate
  • Public Transport Usage
  • Public-Private Partnership Investment
  • Real Interest Rates
  • Risk of Exposure to Natural Disaster
  • Risk of Terrorism
  • Risk Premium
  • Student - Teacher Ratio in Primary Education
  • Suicide Mortality Rate
  • Survival Rate for Primary Level Education
  • Survival Rate for Secondary Level Education
  • Sustainable Access to Improved Sanitation
  • Sustainable Access to Improved Water Sources
  • Sustainable Access to Safely Managed Sanitation
  • Sustainable Access to Safely Managed Water Sources
  • Think Tank Prevalence
  • Total Municipal Spend on Research and Development
  • UNESCO Sites
  • Unrestricted Business Collaboration
  • Venture Capital Investment
  • Voter Participation
  • Wonders of the World
  • Youth Crime Rate
  • Youth Suicide Mortality Rate
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