Without a team of researchers, nor the budget of a multinational, I have relied on the Innovation Cities Index to narrow down the pool to a manageable list of cities to rank.
Innovation Cities collects more than 160 indicators on innovation in global cities and then provides a ranking. I believe that a smart city must be an innovative city. So in order to be considered in the Asia/Pacific smart cities rankings, the city must have achieved a Top 100 global ranking in the Innovation Cities Index. This narrowed down the potential candidates to 17.
Once I had the 17 cities for consideration, I leveraged the Smart Cities Wheel to search for databases with comparative data on essential components. Below is a table that summarizes the secondary data sources used to benchmark and rank Asia/Pacific smart cities.
Table 2: Data Sources
| Component |
Publisher |
Description |
Notes |
Links (where applicable) |
| Smart Economy |
Brookings |
Brookings Institute researches economic growth rates in 300 of the largest cities across the globe. |
|
Global MetroMonitor 2012 |
| Smart Environment |
Siemens |
Siemens developed the Green Cities Index for most major regions including Asia. |
Premier ranking of green cities in Asia but does not include Australian and New Zealand cities. |
Siemens Green City Index |
|
Other |
CO2 per capita |
Using Siemens data and data from other sources, to obtain CO2 per capita for each city. |
|
| Smart Governance |
Rutgers |
Gathered data on 100 major cities to assess security, usability, and content of municipal websites; the type of online services currently being offered; and citizen response and participation through websites established by municipal governments. |
While the researchers have not yet published their latest ranking, they were kind enough to provide me an advanced copy for use in this report. |
N/A |
|
Carbon Disclosure Project |
The CDP recently launched a standard for cities to transparently report their carbon footprints. |
Note, the use of CDP for cities reporting was a binary measure in this study (yes/no) as a proxy for levels of transparency in cities. |
CDP Results |
| Smart Living |
Mercer |
Mercer measures a range of indicators on the quality of life in cities around the globe. |
|
Mercer's 2012 Quality of Living Survey Results |
| Mobility |
Siemens |
Green Cities Index contains analysis of 3 aspects of municipal transit. |
Cities are grouped into 4 different categories depending on their performance on those 3 aspects of municipal transit. |
Siemens Green City Index |
|
Other |
I used multiple sources to obtain information on public transit ridership per capita. |
It is surprisingly difficulty to obtain comparable data on transit ridership across cities in the region. Ideally, would like to add non-motorized transit but data not widely available. |
N/A |
Applying the Smart Cities Wheel
Whenever possible, I identify robust sources of data that have in themselves utilized multiple indicators to assess one component of the smart cities wheel.
Smart Living is measured very well by Mercer's annual Quality of Living rankings. Mercer uses 39 criteria across health, crime, education, climate, and other categories to rank the quality of life in more than 200 cities each year.
The same goes for Citigroup's Hotspots report and its application to the Smart People component. The Hotspots report "compares 200 of the world’s major urban agglomerations across eight distinct categories of competitiveness and 31 individual indicators." I used Citigroup's Human Capital dimension as the lone metric for Smart People.
I sought to use the same data source to compare all cities in the study. Unfortunately, that was not always possible, so I had to use multiple sources. This opens up the risk that some of the data is not perfectly comparable. This occurred, for example, in the analysis of Smart Mobility. While Mobility is one of the categories of the Siemens Green City Index -- a great resource for comparing cities on sustainability -- this study did not include cities from Australia and New Zealand in its ranking. Therefore, I found additional information about mobility in these cities. (I sought, but was unable to obtain, comparable data on non-motorized transit use in the Asia/Pacific region. I believe high rates of non-motorized transit [e.g., walking and cycling] demonstrate smart urban planning.)
While the data used here is secondary, this methodology leads to quality results and opens up the discussion of what makes a city smart, allowing us to begin benchmarking and sharing information across cities around the world.
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