1. Iowa Science City Scorecard Case
Study: An application of the
Stifterverband‘s Science Scorecard for
the university cities of Iowa
April 2015
2. “Science” Scorecard Background
• Rankings, indexes, and scorecards provide an effective
tool for breaking down big data for easier analysis and
depiction
• The science scorecard is a policy tool tor measuring and
identifying the potentials and challenges in each actor’s
respective city. This tool can be used to help cities design
best practices for strategic knowledge based community
development.
3. “Science” Scorecard Concept: Knowledge Based
Community Development
• The science scorecard is made up of two components: the
regional profile (quantitative indicators) and the region in
action (qualitative indicators)
• The city profile empirically measures the performance of
each city based on its economy, science presence, and
community strength
• The city in action provides a closer in depth look at the
current processes taking place to strengthen the city
through knowledge based development.
4. The Science Scorecard ranks cities based on quantitative and
qualitative factors.
CityinAction
Strategy
Policy
Framework
Community
Engagement
Transfer
Networks
Innovation
Culture
Collaboration
Platform
Structure
Branding
Science Brand
City Brand
Knowledge
Retention
Education
City
Attractiveness
CityProfile
Science
Institution
R&D
Tech Transfer
Community
Demographics
Infrastructure
Economy
Potential Growth
Startup Culture
Workfoce
Indicators
Bildung
CityObjectives
6. Science Indicators
University
• Bachelors of Science
Degrees Conferred
• International Student
Population
• R&D personnel per
student
R&D
• Government R&D
expenditure per
student
• Institution R&D
expenditure per
student
• Business R&D
expenditure per
student
Tech Transfer
• University spinoffs
• University Sponsored
Research
Park/Incubator Growth
Rate (companies)
• University Sponsored
Research
Park/Incubator Growth
Rate (employees)
• Patents per 1,000 jobs
7. Institution Indicators
• Institutions play a vital role in providing a skilled workforce,
contributing to knowledge spillovers, and supplying firms
with cutting edge research
• STEM degrees are essential for providing the labor
market with highly skilled knowledge workers
• International students bring diversity, new ideas, and play
a key role in knowledge diffusion
• University R&D is plays a key role in providing small firms
the information they need to commercialize knowledge
and succeed
8. R & D Indicators
• New economic knowledge is captured by R&D thus cities
that want to attract high tech clusters and promote job
growth need to have a strong presence of university,
government, and private R&D along with skilled workers
(Audretsch & Feldman)
• According to the Small Business Administration research
universities and their investment play a significant role in
contributing to economic growth and the regional labor
market (SSTI)
9. Tech Transfer
• University spinoffs are generally in highly paid STEM
fields.
• University research parks/incubators provide specialized
support which has the tendency to attract firms and lead to the
development of commercialized technologies which result in
new business startups
• These research parks promote industry clustering which
benefits these businesses by reducing costs of finding skilled
labor and transaction costs between firms; increasing
productivity and income
• University students and employers mutually benefit from
apprenticeship programs which provide the company with new
innovations and the students with technical experience
10. Community Indicators
Demographics
• Population Density
• Population Growth
• Proportion of Foreign Born Residents
Infrastructure
• Gross Median Monthly Housing Costs
• City Funds Dedicated to Transit
Improvement per Resident
• School District College Readiness Score
11. Demographic Indicators
• High population density and strong population growth
facilitates more face to face interaction which von Hipple
(1994) demonstrated was key for high tech knowledge
transfer
• In Richard Florida’s “3 T’s” model of economic growth
technology, talent & tolerance are all interrelated
• Foreigners bring in new ideas and perspectives and
provide diversity which makes cities more attractive for the
creative class
• High-tech workers correlate with the creative class, the
Talent Index and other diversity resources (18)
12. Infrastructure Indicators
• High housing costs forces local employers to increase
wages and in the long run dampens economic growth,
because these costs raise the compensation it takes to
attract and retain workers (2-3)
• Over-regulation and restriction of housing supply can lead
to high housing costs and income inequality especially in
university cities (62)
• A study by the US Chamber of Commerce found that in
the short run, a dollar spent on infrastructure construction
produces roughly double the initial spending in ultimate
economic output (10)
13. Infrastructure Indicators
• Munnel’s study found that more investment in infrastructure
tends to be associated with greater output, more private
investment and more employment growth
• According to Glaeser, highly educated parents are attracted
to places that can provide a top notch education for their
children
14. Economy Indicators
Potential Growth
• Small Firms
• Resident Firms
• High Tech
Firms
Startup Culture
• New Startup
Growth
• Firm move-in
Rate
• Small Business
Innovation
Research
Awards
Workforce
• Population
holding
Bachelor’s
Degree or
Higher
• Workers
Holding a
STEM bachelor
degree
• Tech Workers
Productivity
• Real GDP per
capita
• GDP per
worker
• Unemployment
Rate
15. Potential Growth Indicators
• The Small Business Administration found that over 90% of high
impact firms had fewer than 20 employees (11)
• Small and young businesses are the primary source of jobs in the
US
• High tech firms are responsible for approx. 60% of private sector
R&D and are important for local knowledge spillovers (17)
• Although new startup firms have a high failure rate, high tech and
ICT startups outpace their failure rate by double and grow more
rapidly than non-tech new firms (17)
• Additionally, high tech jobs are associated with job creation. For
every 1 high tech position there are 4 additional jobs in the local
services economy in the region (17)
16. Startup Culture
• Entrepreneurship is positively correlated with measures of
economic growth. Audretsch found that higher
entrepreneurial activity is clearly linked to lower rates of
unemployment (26)
• The number of move-in firms is used to show the strength
of the city’s business environment.
• Awards from the Federal’s Small Business Innovation
Research is an indicator for the success of local business
innovation.
17. Workforce & Productivity Indicators
• A highly skilled technical workforce is an essential
component for achieving a tech based economy (7)
• The number of workers in the technology field is a proxy
for the number of highly qualified workers. A higher
number of qualified workers concentrated in one place is
associated with increased productivity.
• Per capita GDP per worker is a well known indicator for
measuring productivity and is positively correlated with
economic growth.
18. City in Action
I. Strategy
Policy
Framework
Community
Engagement
II. Transfer
Networks
Innovation
Culture
III.
Collaboration
Platform
Structure
IV. Branding
Science Brand
City Brand
V. Knowledge
Retention
Education
City
Attractiveness
The Qualitative Factors
20. City Goals
Ames
• Promote economic development through developing a brand
communication plan
• Identify characteristics that support ISU Technology Transfer
• Address housing needs i.e. availability and affordability
Cedar Falls
• Explore the potential of intergovernmental cooperation options
• Support economic efforts that attract, retain and create quality
jobs resulting in a diverse economic base and increased
population.
Des Moines
• Promote economic stability, growth and vitality
• Improve and enhance community communications
• Maintain and enhance the city's infrastructure
Iowa City
• Strong urban core
• Strategic economic development activities
• Enhance community development
21. Science City Scorecard: Ames
Science
70.37%
Community
58.63%
Economy
56.53%
Strategy
87.5%
Transfer
81.25%
Collaboration
100%
Communication
75%
Knowledge
Retention
62.5%
22. A Closer Look: Ames
Strengths
+ Strong research tradition
+ Highly skilled workforce
+ Robust networks
+ Recognized place
branding
Weaknesses
- Knowledge retention
-Low spinoff growth
23. Science City Scorecard: Cedar Falls
Strategy
75%
Transfer
87.5%
Collaboration
91.6%
Communication
37.5%
Knowledge
Retention
75%
Science
37.25%
Community
31.19%
Economy
26.07%
24. A Closer Look: Cedar Falls
Strengths
+ Startup culture
+ Strong partnerships
+ Knowledge Retention
Weaknesses
- Lack of science presence
- Underinvestment in R&D
- Low density of small &
local firms
25. Science City Scorecard: Des Moines
Strategy
37.5%
Transfer
81.25%
Collaboration
66.67%
Communication
50%
Knowledge
Retention
100%
Community
34.79%
Science
32.96%
Economy
33.18%
26. A Closer Look: Des Moines
Strengths
+ Strong community
networks & social services
+ Attractive region
Weaknesses
- Knowledge transfer
-Presence of skilled
workers
-Low R&D investment
27. Science City Scorecard: Iowa City
Strategy
12.5%
Transfer
62.5%
Collaboration
100%
Communication
68.75%
Knowledge
Retention
62.5%
Community
80.38%
Science
72.04%
Economy
43.55%
28. A Closer Look: Iowa City
Strengths
+ Strong research tradition
+ Highly skilled labor pool
+ Regional attractiveness
Weaknesses
- Innovation culture
- Incorporation of science
into strategic plan
31. Data Methodology
• Raw data was collected from highly recognized sources
i.e. US Census Bureau, Iowa Board of Regents, National
Science Foundation etc.
• Data was then standardized for each indicator and
transformed into an index score
• An indexed score for each indicator was calculated using
the following method:
Example: population growth
(ln city_value – ln min_value) / (ln_max_value – ln min_value) = X
32. Original Data: Science Indicators
Science_Indicators Ames CF DSM IC
% of bachelors degrees conferred in science, technology, engineering, agriculture, and
mathematics 0.44 0.03 0.16 0.22
% of international students 0.11 0.05 0.03 0.08
% R&D personnel of student pop. :2013 0.18 0.02 NA 0.21
Government expenditure on R&D per student 4.77 0.22 0.15 8.32
Institutional expenditure on R&D per student 2.44 0.07 0.05 4.46
Business expenditure on R&D per student 0.53 0.006 0.002 0.47
Number of startup companies formed in total (2011-2013) (uni spinoffs) 5 222 NA 22
Research Parkincubator growth rates (companies) 0.12 0.21 NA 0.19
Research Parkincubator growth rates (employees) 63.45 24.48 NA 0.006
Patents/1000 jobs (2007-2011) 5 year average 1.30 0.40 0.70 0.70
33. Original Data: Community Indicators
Community_Indicators Ames CF DSM IC
Population density 2552 1410 2566 2863
City growth rate 0.048 0.033 0.016 0.054
% Foreign born residents 0.112 0.058 0.111 0.142
Gross median monthly housing costs $ 807 828 863 919
City funds dedicated to transit improvement per resident
in $ 198 143 61 104
Education: US News College Readiness Score (2011-
2012) 40.4 28.1 11.1 30.8
34. Original Data: Economy Indicators
Economy_Indicators Ames CF DSM IC
Ratio of small firms to total firms 0.636 0.618 0.597 0.677
Ratio of resident firms to total firms 0.894 0.887 0.903 0.897
Ratio of high tech firms (Code:31,51,54) to total firms in all
industries (2012) 0.169 0.136 0.162 0.133
% of new startups growth from 2000-2013 0.053 0.001 0.074 0.603
% growth of new move-ins 2000-2013 0.037 0.023 0.015 0.091
# SBIR awards, 2011 7 2 4 0
% of population ( 25 yrs +) holding bachelors degree or
higher 0.618 0.441 0.297 0.58
% of workers in tech, 2011 0.026 0.018 0.033 0.037
% of workers with STEM bachelors 0.187 0.066 0.094 0.097
Per capita real GDP(chained 2009 dollars) (2013) 50302 47748 66212 49475
Per capita GDP per worker, 2011 71882 80386 96207 70776
Unemployment rate 0.023 0.029 0.039 0.025
35. Further Data Analysis
*Am currently working on putting together a storyboard on
Tableau which will go here.
- It will include an overall analysis of the different patterns
found in the data as well as several heat map pictures
36. Next Steps…
• Expand study to include all cities with AAU institutions in
the Midwest or adapt index for MSAs
• Create an interactive scorecard to be used as an
analytical tool for each city
38. How it Would Work
City Selection Goal Selection
City Profile City in Action
Characterisitics
Population 100.000
Students 20.000
…
1) Economic growth
2) KnowledgeTransfer
3) Diversity
…
Factor 1 56/100
Factor 2 0/100
Factor 3 80/100
Factor 4 66/100
Question 1 0/4
Question 2 2/4
Question 3 4/4
Question 4 3/4
Analysis & Best Practice Methods
39. Lessons for Germany
Science and entrepreneurship are critical factors to improving
regional economies. Iowa is mostly rural yet its university cities
have become hubs for innovation in business, agricultural
sciences, engineering, and data science. By providing access to
high speed internet, co-working spaces, business incubators,
research parks, and venture capital, these cities have created a
business friendly climate for firms of all sizes. Additionally, the
robust extension programs of the public universities has resulted
in knowledge spillovers and job creation. By deregulating internet
laws and making high speed internet connection a priority in rural
areas Germany could diversify and strengthen its economy. Also,
by establishing university extension programs German cities can
increase knowledge transfer which results in more jobs.
Editor's Notes
The city has more control over the processes considered in the city in action component. Both components of the scorecard are complementary and together provide a better depiction of each city. By including and measuring a qualitative component, the science scorecard is distinct from other rankings and is especially useful for policymaking.
There are two dimensions to the science city scorecard: the quantitative and qualitative parts that link the city objectives.
Make smaller and add source.
Supporting Literature:
1. A Resource Guide for Technology-based Economic Development. (2006)State Science and Technology Insitute (11).
2. Yingitcanlar,Tan and Baum,Scott andHorton, Stephen (2007) Attracting and Retaining Knowledge Workers in Knowledge Cities(23);Ergazakis.(2006) Knowledge Cities.
3. R&D Spillovers & Geographic Innovation & Production. Audretsch. (639).; Wolfgang G. Stock (2011) Informational Cities(974)
Supporting Literature:
R&D Spillovers & Geographic Innovation & Production. Audretsch. (639)
Informational Cities. (2007) Wolfgang G. Stock.
A Resource Guide for Technology-based Economic Development. (2006)State Science and Technology Insitute (11, 64).
Supporting Literature:
Tech Starts: High Tech. Business Formation & Job Creation in the US. (2); Benneworth (5,12-13, 17)
Software, Creativity & Economic Geography.Florida.2003.(3)
UNI Report (6)
A Resouce Guide for Technology Based Economic Development (2006) (7, 37)
Software, Creativity & Economic Geography. (2003) Florida. (3)
Portland Entrepreneurship Scorecard (2011) (4)
Supporting Literature:
Linking Entrepreneurship to Growth. Audretsch. (15)
Triumph of the City. Glaeser.
Software, Creativity & Economic Geography.Florida.2003.(4)
S. Musterd & O.Gritsai(2010)Conditions for Creative Knowlede Cities(9)
Boschma(2009)Creative Class and Regional Growth
Willem van Winden (2009)European Cities in the Knowledge Economy(535).
Supporting Literature:
Workforce Housing Report.(2008) Michael Carliner.(2-3);
How Does Public Infrastructure Affect Regional Economic Performance? Alicia Munnell.(2);
Triumph of the City. Glaeser.
Supporting Literature:
How Does Public Infrastructure Affect Regional Economic Performance? Alicia Munnell.(2);
Triumph of the City. Glaeser.
Supporting Literature:
Portland Entrepreneurship Study (2011) (4,)
Linking Entrepreneurship to Growth. Audretsch.(16).
Used by Your Economy (University of Wisconsin-extension) these firms typically have more influence on job creation than non-resident firms.
Tech Starts: High Tech. Business Formation & Job Creation in the US. (2, 16, 17).
Creative Class and Regional Growth. (2009) Boschma (417)
Informational Cities. (2011) Wolfgang G. Stock (981).
Supporting Literature:
Tech Starts: High Tech. Business Formation & Job Creation in the US. (2)
Linking Entrepreneurship to Growth. Audretsch. (29)
Portland Entrepreneurship Scorecard (2011) (4)
Supporting Literature:
Software, Creativity & Economic Geography. (2003) Richard Florida.(3,18)
Workforce Housing Report. (2008) Michael Carliner. (62)
A Resource Guide for Technology Based Economic Development(2006)(7).
Informational Cities. (2011) Wolfgang G. Stock. (971)
European Cities in the Knowledge Economy. (2009) Willem van Winden et al. (535)
Strategy: the actors in the city work together to formulate and integrate strategies to develop strong scientific initiatives into their policy framework while also engaging the community
Transfer/Networks: policymakers, business leaders, and university officials work together to strengthen networks and facilitate knowledge and technology transfer
Collaboration: all stakeholders work together to provide a platform and structure for promoting science as a driver of economic development i.e. public lectures, inter-disciplinary projects, internship opportunities
Branding: this category measures the extent to which the city is known for being a science location as well as the city’s general visibility
Knowledge retention: this measures how well the city retains knowledge workers and the overall attractiveness of the city i.e. cultural events, human services, etc.
The university cities of Iowa were chosen as a case study model for the original scorecard because of the similar challenges and opportunities faced by policymakers in Geman cities. One problem faced by some German university cities is brain drain. Often times students migrate to other states with bigger cities like Berlin that provide better job opportunities. Similarly, Iowa university towns like Ames produce highly skilled science graduates but these students leave Iowa for places like Silicon Valley or Austin, Texas. Also similar to Germany, Iowa university cities struggle to create a strong brand image to attract more businesses and to increase their reputation. Iowa is commonly viewed as being rural and “in the middle of nowhere” by many people in the US thus these cities are working hard to rebrand themselves. Additionally university cities in Iowa and Germany both are working to facilitate knowledge transfer through strong public-private networks and to foster entrepreneurship and job creation via university startups and businesses.
Adjust scores.
The city of Ames has a reputation for being a strong community while the university is world renown for its science and technology research especially in the agricultural sciences. The high science and community scores confirm this reputation. However, the city needs to continue to work to attract more international students and the university needs to promote more spinoffs. Currently, the majority of innovations by university researchers are transferred and used by established public and private entities. To strengthen the economy, the city needs to work on improving its business environment to attract more small firms and create a city environment that draws more tech workers to meet the skills required by its growing technology sector. While ISU produces many skilled graduates, it loses them to other cities.
This small university city is regionally known for its startup culture. The city has formed a strong partnership with Waterloo to increase knowledge transfer and job creation. To increase its science presence and promote economic development, the university needs to hire more R&D personnel, as well as, invest in R&D. Additionally, the Cedar Falls Community School District needs to work on better preparing their students for college. Also Cedar Falls must work to strengthen their brand image. Many times Cedar Falls is overshadowed by Waterloo. Although the University of Northern Iowa produces the majority of startups and university spinoffs in Iowa, it has a low presence of these small and local firms. It tends to be dominated by larger firms. City actors should make sure that current policy and city environment is conducive to retaining small businesses.
Des Moines is a vibrant capitol city constantly ranked as an up and coming city by Forbes magazine and others. It has strong community networks and caters to the needs of young knowledge workers. However, Des Moines is devoid of research parks and business incubators that facilitate knowledge transfer and job creation. Currently the city of Des Moines is reliant on the the Research Park in Ames. To further expand their potential the city could encourage business incubators through tax incentives. Additionally, more emphasis should be placed on collaboration between the universities, city, and businesses. One way to increase collaboration would to include university students on city boards and the chamber. The city of Ames currently allows a student to serve on the city council and actively seeks out students to serve on the various boards, as well as, providing internship and service project opportunities.
Iowa City is known for its strong research and high ranked medical school and law school. It is a very attractive city for young people to live and is well known for its cultural events. Iowa City has a strong sense of community and science presence. However, there is not a clear strategic plan for embedding science and knowledge transfer into the city’s objectives. However, the city suffers from low productivity and a lack of innovation culture. With the university being the largest employer, many young graduates seek work elsewhere. To diversify possible employment, the city should work more closely with companies and the university to promote entrepreneurship and create a startup friendly culture.
Max and min values were taken from the sample data.
The cockpit provides an overview of all of the cities analyzed and allows you to compare each city. While the dashboard is city specific and provides a snapshot and performance measurement for each category. The last page can be used to interpret the data.
The interactive scorecard is built on a user friendly Excel interface. Each goal is linked to corresponding factors in the city profile and city in action which can be used to measure the city’s progress in achieving these goals.
