the top 100 cities primed for smart city...

The Top 100 Cities Primed for Smart City Innovation

THE TOP 100 CITIES PRIMED FOR SMART CITY INNOVATION Identifying U.S. Urban Mobility Leaders for Innovation Opportunities

6 March 2017

Prepared by

The Top 100 Cities Primed for Smart City Innovation | 1

1. OVERVIEW Cities are becoming smart. By investing in solutions that take advantage of the potential of big and open data to increase efficiency, cost savings, and opportunities for the public, cities are rapidly transforming into “smart cities.” But with over 90,000 local governments in the U.S., how do you know what cities will benefit the most from smart city initiatives? Here at CivicConnect we set out to answer that question, with a special focus on smart mobility. Taking an analytical approach, we identified and ranked 100 cities that would be the best candidates for smart cities initiatives. We also profiled the differences between the best candidates and the rest of the cities and the implications of those differences.

2. OUR APPROACH To identify smart cities, we selected 10 criteria that represented smart city characteristics. The 2010 U.S. Census was the primary data source, supplemented by the 2015 National Transit Database, USDOT Smart Cities Challenge, and Association of Metropolitan Planning Organization’s 2013 Spending Report.

Table 1 Smart city criteria by category

CATEGORY VARIABLE SCORINGCRITERIA

Population Characteristics

Size > 500,000 residents

Growth > 2% projected growth

Density > 2 million in Core Based Statistical Areas

Local Spending

Local transportation+transit spending amount ($)

> $5 billion in local transportation spending for entire state

Local transportation+transit spending commitment (%)

> 5% local transportation spending of total spending

Regional involvement Top 25 spending Metropolitan Planning Organizations (MPOs)

Transportation Interest

Complexity > 1 mode of transit reporting to National Transit Database

Transit ridership > 2 million unlinked passenger trips

Smart City Interest Leadership Employs a CIO (or similar position)

Activity Applied to USDOT Smart Cities Challenge

An initial list of the 285 largest (based on population size) incorporated communities in the U.S. was extracted from the 2010 U.S. Census. Using that list as a foundation, one point was assigned


to each city if it met the criteria. This point system does not weight one variable over the other, but rather measures each qualification equally.

3. ANALYSIS AND FINDINGS Table 2 Number of cities by smart city score

This analysis identified 103 smart cities.* We determined that a score of four or more was considered a smart city, meaning that a city must meet at least four of the qualifications this analysis considered important to defining a potential smart city. Note that some scores resulted in a tie, leaving 103 cities classified as smart cities in our Top 100 list. This results in 36 percent of the cities analyzed being identified as smart city candidates. No city analyzed earned all 10 points. Chicago and New York City both earned the most amount of points with a score of nine, with Boston, Denver, Los Angeles, and Riverside following closely with a score of eight. A concentration of cities (24 percent) were close to achieving smart city recognition with a score of three points.

Although there is a somewhat diverse geographic spread, the cities display a clear cluster in the west (40 percent) and south (33 percent) ( Figure 1). The map on the next page displays in more detail the geographic spread of the cities analyzed and their smart city scores. The darker the circle, the higher the smart city score. As can be seen, there are large concentrations on both the west and east coast. Among the most populated states in the U.S., it is not surprising that California (25), Florida (8), and Texas (8) have the largest number of smart cities recognized in this research.

Figure 1 Percent of recognized smart cities by region

*For the complete list of smart cities from our analysis, please contact us at [email protected]

SCORE COUNTOFCITIES

PERCENTOFCITIES

9 2 1%8 4 1%7 18 6%6 14 5%5 22 8%4 43 15%3 67 24%

2 71 25%

1 40 14%

0 4 1% Total 285 100%

11%

17%

33%

40%

Northeast

Midwest

South

West


Figure 2 Geographic spread of identified smart cities based on analysis


2.1 SMART CITY AND MOBILITY MARKET

Using the 2013 and 2014 Annual Surveys of State and Local Government Finances data, we performed a high-level smart city market sizing and segmentation of the 285 cities recognized in our analysis. We found that in 2013 and 2014, local governments in these 285 cities spent a total of $1.4 trillion annually. Of that, education comprised the largest spending category at 41 percent of total budget and social services was second with 13 percent. Nine percent ($137.6B) of total spending went toward transportation and transit projects. While that may appear like a low amount of spending, smart mobility projects may be funded through other sectors, such as government administration, environment, or public safety.

3. SMART CITY PROFILE Looking at demographic, transportation and spending characteristics, we developed a high-level smart city profile by comparing our identified smart cities to average U.S. characteristics. As can be seen in the table below, the recognized smart cities are younger and driving less in favor of other modes of transportation for commuting. Additionally, these smart cities had higher transportation expenditures. (Note: transportation spending can vary significantly year to year due to external factors such as weather, grant funds, and programmed projects.)

Table 3 Comparison of general U.S. and identified smart city characteristics

CHARACTERISTIC U.S.(2010) SMARTCITIES(2010)Median Household Income $49,445 $48,542 Average Commute Time (mins)

25.9 24.3

Median Age 37 33 Percent Local Transportation + Transit Spending (2013) 12% 24%

Percent Personal Vehicle 86% 82% Percent Public Transit 5% 8% Percent Active 3% 5% Percent Work from Home 4% 4%

Figure 3 Local government spending by sector (source: 2013 Census Annual Survey of State and Local

Finance)


4. IMPLICATION OF RESULTS The results of this analysis show that smart cities have distinguishing characteristics that can be used to better advance and fit smart city, and more specifically smart mobility, initiatives.

If you would like more information on the cities identified in this smart city analysis, please contact us at [email protected] to learn more.

Younger Adults Smart city efforts will need to consider changing millennial travel behavior and patterns.

Driving Less Smart city efforts will need to accommodate multi-modal travelers as well as provide solutions for cities with complex transport-ation systems.

Regional Clustering Smart City efforts will need to reflect regional priorities and characteristics.

Millennials… • Want more reliable systems • Travel using multiple modes • Choose cost-savings and

convenience Source: APTA (2013) “Millennials & Mobility: Understanding the Millennial Mindset” Multi-modal considerations… • Equitable mode choices • Real-time data for users and

operators • Infrastructure needs Regional issues… • Intermodal integration • Economic development and

opportunity • Emerging megaregions

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