This document discusses several papers in a special issue of the Journal of Innovation on smart cities. It summarizes key points from each paper, which address topics like assessing the economic impacts of smart urban attributes, using communities of practice to develop e-government services, modeling smart city performance, the relationship between innovation and knowledge-intensive services in cities, conceptualizing cities as parts of networks, and the efficiency of ethnic entrepreneurs in urban economies. The special issue provides a forum for discussing urban challenges and strategies for improving social science knowledge and setting a European research agenda on smart cities.

4. EUROPEAN JOINT
4 COORDINATION
3
2
1 LOCAL WEAK
COORDINATION

5.  Gibbons/Novotny
Mode 1
Mode 2
 Implications for Urban Policy

6. University University
Knowledge Learning
Industry Government
Industry Government Market

7. Helix Spider
We believe a city to be smart when
investments in human and social capital
and traditional (transport) and modern
(ICT) communication infrastructure fuel
sustainable economic growth and a high
quality of life, with a wise management of
natural resources, through a participated
governance. (Caragliu, Del Bo and Nijkamp,
2011).

8.  9 cities (Bremerhaven, Edinburgh, Karlstad, Kristiansand,
Lillesand, Groningen, Kortrijk, Osterholz, and Norfolk
county)
 Domains:
• e-gov and ICTs
• GDP and income
• Population and density
• Employment and Human Capital
• Infrastructure
• Business
• Local Government
• Tourism and cultural heritage
• Leisure and recreation
 Urban Audit
 Collection of data: direct contact with city officials and
statisticians

9. A special issue on the Journal of Urban
Technology (“Smart cities”)
A book chapter (A.Caragliu, M.Deakin,
C.Del Bo, S.Giordano, K.Kourtit,
P.Lombardi, P. Nijkamp, “An advanced
triple-helix network model for Smart Cities
performance”, IGI Global)
A special issue on Innovation

10.  Baseline datato used to calculate the Knowledge
Economy Indicator for the 9 Smart Cities include:
• The Economic Incentive and Institutional
Regime
• Education and Human Resources
• The Innovation System
• ICTs
 We then normalized the indicators according to
the formula in the next slide

11. 1) The actual data (u) is collected from urban datasets
2) Ranks are allocated to cities based on the absolute values (actual data)
that describe each and every one of 6 variables (rank u). Cities with the
same performance are allocated the same rank. Therefore, the rank
equals 1 for a city that performs the best among those in our sample on
a particular variable (that is, it has the highest score), the rank equals to
2 for a city that performs second best, and so on
3) The number of cities with higher rank (Nh) is calculated for the whole
sample
4) The following formula is used in order to normalize the scores for every
city on every variable according to their ranking and in relation to the
total number of cities in the sample (Nc) with available data :
Normalized (u) = 10*(1-Nh/Nc)
5) The above formula allocates a normalized score from 0 to 10 for each
city

12. 10
9
8
7
6
5
4
Knowledge Economy Indicator
3 Smart cities KEI
2
1
0

13. University
60.0
50.0
40.0
Knowledge 30.0 Learning
20.0
10.0
EU27
0.0
Smart Cities
Government Industry
Market

15.  But, if we de-construct the average Smart Cities value
and zoom in on each of the nine cities, we obtain
markedly different results: Results are rich and difficult to
compare; a more detailed
analysis is needed.
University
Knowledge Economy 3,0 Bremerhaven
2,5 i2010
Indicator 2,0 Edinburgh
1,5
1,0 Karlstad
Knowledge 0,5 Learning
0,0 Kristiansand
-0,5
-1,0
-1,5 Lillesand
e-services -2,0 Intellectual property
Groningen
Kortrijk
Government Industry
Osterholz
ICT-related Norfolk
RTD
employment
EU27
Market
SCRAN

16. University
Knowledge Economy 2,5
Bremerhaven
2,0 i2010
Indicator
1,5
EU27
1,0
Knowledge 0,5 Learning
0,0
-0,5
-1,0
e-services -1,5 Intellectual property
Government Industry
ICT-related employment RTD
Market

17. University
Knowledge Economy 2,5
2,0 i2010 Edinburgh
Indicator
1,5
Knowledge 1,0 Learning
0,5 EU27
0,0
-0,5
e-services -1,0 Intellectual property
Government Industry
ICT-related employment RTD
Market

18. University
Knowledge Economy 2,0
i2010
Indicator 1,5
1,0 Karlstad
Knowledge 0,5 Learning
0,0
-0,5
EU27
e-services -1,0 Intellectual property
Government Industry
ICT-related employment RTD
Market

19. University
1,0 Kristiansand
Knowledge Economy
0,8 i2010
Indicator 0,6
0,4 EU27
Knowledge 0,2 Learning
0,0
-0,2
-0,4
-0,6
e-services -0,8 Intellectual property
Government Industry
ICT-related employment RTD
Market

20. University
Knowledge Economy 3,0 Lillesand
2,5 i2010
Indicator 2,0
1,5
Knowledge 1,0 Learning EU27
0,5
0,0
-0,5
-1,0
e-services -1,5 Intellectual property
Government Industry
ICT-related employment RTD
Market

21. University Groningen
Knowledge Economy 2,5
2,0 i2010
Indicator 1,5 EU27
1,0
Knowledge 0,5 Learning
0,0
-0,5
-1,0
-1,5
e-services -2,0 Intellectual property
Government Industry
ICT-related employment RTD
Market

22. University
2,0
Knowledge Economy Indicator i2010 Kortrijk
1,0
Knowledge Learning EU27
0,0
-1,0
e-services -2,0 Intellectual property
Government Industry
ICT-related employment RTD
Market

23. University
Knowledge Economy 2,5 Osterholz-Scharmbeck
2,0 i2010
Indicator
1,5 EU27
1,0
Knowledge 0,5 Learning
0,0
-0,5
-1,0
e-services -1,5 Intellectual property
Government Industry
ICT-related employment RTD
Market

24. Norfolk
University
Knowledge Economy 2,5
2,0 i2010
Indicator EU27
1,5
1,0
Knowledge 0,5 Learning
0,0
-0,5
-1,0
-1,5
e-services -2,0 Intellectual property
Government Industry
ICT-related employment RTD
Market

25. Indicators for the New Triple Helix
Variable Measure Notes
University (% people aged 20-24 enrolled
University
in tertiary education)
Learning ( labour force with ISCED 5 and
Learning
6 education)
Industry (Number of companies per
Industry
1,000 pop.)
Market Market (Per capita GDP)
Government (% labour force in
government sector-L to Q: Public
Government administration and community services;
activities of households; extra-territorial
organizations )
Knowledge (Patent applications to the
Knowledge
USPTO per 1,000 inh.)
Per capita number of administrative
e-services forms available for download from official
web site
Number of local units manufacturing ICT For the EU, % of GDP produced by the
ICT-related employment
products over total active companies ICT industry
Source: NUTS1/2 data from the Regional
Business R&D expenditure Business R&D expenditures (2006)
Innovation Scoreboard 2009
Number of patent applications to the
Co-patenting between industry and
Intellectual property USPTO shared by at least one company
universities
and one university since 1977.
http://info.worldbank.org/etools/kam2/K
Knowledge Economy Indicator Average World Bank KEI score
AM_page5.asp
Municipal scores calculated by the
i2020
Edimburgh team.

26. References
1. Caragliu, A; Del Bo, C. & Nijkamp, P (2011).
“Smart cities in Europe”, Journal of Urban
Technology, forthcoming
2. A. Caragliu, M. Deakin, C. Del Bo, S. Giordano,
K. Kourtit, P. Lombardi, P. Nijkamp (2011). “An
advanced Triple-Helix network model for
smart cities performance”, in O. Yalciner
Ercoskun (ed.), “Green and ecological
technologies for urban planning: creating
smart cities”, Hershey (PA): IGI Global

27.  Performance: ratio between input and output
 DEA: comparative analysis

30. Great variety in smart cities
Relevance of multiple helix
Meaning of performance analysis
Message:
reinforce strong points and address weak
points

31.  Editors:
Karima Kourtit &
Peter Nijkamp
 No. 4, 2011
 Published by Taylor &
Francis (UK)

32. manage develop a
design a spatially- sustainable develop an effective balanced
manage
turn mass
integrated and accessibility policy to ensure that national (or
production and
population the benefits of supra-national)
balanced urban and mobility investments to
movement agglomeration strategy for
land use strategy towards urban of urban the benefit of
that is compatible agglomerations systems advantages are emerging
higher than their connected city sustainable
with ecological through new economic
into new social costs systems
sustainability opportunities logistic and development
infrastructur satisfy the socio- of urban areas
al concepts develop economic demand
need for conflict effective
management and pro-active of an increasingly
design of fit-for-purpose measures for large share of
inclusions strategies for less
institutional mechanisms eco-friendly urban population
privileged groups in urban and climate-
and structures in a multi- for high-quality
areas neutral
layer dynamic system of urban amenities
urban areas metropolitan
areas

33.  Improvement transport systems & infrastructure
 New information technology
 Climate change
 Demographic transformation
 Increased globalisation
 Rising urbanization in Europe
Regional, national and international competition
push cities
Cities are in competition in a way that is similar to
competition between companies and products
33 33

34. “Competition among cities is like riding a
bicycle: if you don’t pedal, you’ll fall off”.
However, globalization is making us
increasingly uniform, so we must
construct and promote our difference in
order to continue existing”
Mirón, Urban Land Institute

35. The Special Issue of Journal Innovation on ‘Smart Cities in the
Innovation Age’:
 Provides a unique forum for discussing worldwide urban
challenges and developments
 Addresses in particular the feasibility of smart cities
concepts by presenting a series of applied studies on the
success conditions and implications of smart city strategies
and ideas
 The papers on all aspects of European urban developments
contribute to the improvement of social science knowledge
and to the setting of a policy-focused European research
agenda

36. Table of Contents
1. Smartness and European Urban Performance: Assessing the Local Impacts of
Smart Urban Attributes by Andrea Caragliu and Chiara Del Bo
2. Intelligent Cities as Smart Providers: CoPs as Organizations for Developing
Integrated Models of eGovernment Services by Mark Deakin
3. Modelling the Smart Cities Performances by Patrizia Lombardi, Silvia Giordano,
Hend Farouh and Wael Yousef
4. Is Innovation in Cities a Matter of Knowledge Intensive Services? An Empirical
Investigation by Roberta Capello, Andrea Caragliu and Camilla Lenzi
5. Smart Networked Cities? by Emmanouil Tranos and Drew Gertner
6. Open Innovation Among University Spin-off Firms: What is in it for Them, and
What Can Cities Do? by Marina van Geenhuizen
7. Bright Stars in the Urban Galaxy – The Efficiency of Ethnic Entrepreneurs in
the Urban Economy by Mediha Sahin, Alina Todiras, Peter Nijkamp and Soushi
Suzuki
8. Smart Cities in Perspective − A Comparative European Study by Means of
Self-Organizing Maps by Karima Kourtit, Peter Nijkamp and Daniel Arribas

37. 1. Smartness and European Urban Performance: Assessing the Local Impacts
of Smart Urban Attributes by Andrea Caragliu and Chiara Del Bo:
 Provides a comparative benchmark analysis of the growth
performance of various smart cites in Europe
 Points in the direction of the critical importance of space specific
characteristics in shaping the economic benefits of smart urban
qualities, providing a justification for place-based public policies
that account for local characteristics
 Identifies different clusters with respect to the impacts of
smartness on urban performance and wealth, highlighting the
need for geographically-differentiated policy actions.
2. Intelligent Cities as Smart Providers: CoPs as Organizations for Developing
Integrated Models of eGovernment Services by Mark Deakin
 Analyses the learning aspects of smart cities
 Interprets intelligent cities as facilitators and communities of
practice for designing and implementing e-government services
 Identifies how the growing interest in intelligent cities has led
universities to explore the opportunities „communities of practice‟
(CoPs) offer to industry in order to become smart providers of
online services

38. 3. Modelling the Smart Cities Performances by Patrizia Lombardi,
Silvia Giordano, Hend Farouh and Wael Yousef
 Addresses the assessment and modelling of the performance of
smart cities is an intriguing research challenge
 Proposes a novel research agenda for the development of a testing
exercise with the participation of main city stakeholders, offering a
reflexive learning opportunity for cities to measure what options exist
to improve their performances
4. Is Innovation in Cities a Matter of Knowledge Intensive Services? An
Empirical Investigation by Roberta Capello, Andrea Caragliu and Camilla
Lenzi
 Raises the question whether a high innovation degree in cities is
related to the local presence of knowledge-intensive services
 Argues that the linkage between the presence of cities in the region
and their innovative performance is mediated by the urban industrial
structure
 Argues that a positive correlation is likely to exist between the
presence of large cities in a region and its innovative performance.
Such a relationship could also depend on the presence of knowledge-
intensive services, rather than on advanced manufacturing activities

39. 5. Smart Networked Cities? by Emmanouil Tranos and Drew Gertner
 Argues that cities are part of a broad national or global network, both
physical and virtual
 Investigates conceptually and empirically the issue of smart networked cities
 Argues that the local policy agenda – and more specifically smart city
initiatives – should be informed about and address the structure of the
transnational urban network, as this can affect the efficiency of such local
policies
6. Open Innovation Among University Spin-off Firms: What is in it for Them, and What
Can Cities Do? by Marina van Geenhuizen
 Argues that smart cities are most likely well equipped with an advanced
knowledge infrastructure which may induce important benefits
 Offers a new perspective on the open innovation potential provided by
university spin-off firms
 Examines a particular category of high-tech firms, university spin-offs, and
highlights resources that are missing and the level of openness in learning
networks to gain these resources
 Argues that the vitality of modern cities is nowadays strongly influenced by
cultural diversity

40. 7. Bright Stars in the Urban Galaxy – The Efficiency of Ethnic Entrepreneurs
in the Urban Economy by Mediha Sahin, Alina Todiras, Peter Nijkamp and
Soushi Suzuki
 Argues that the new urban entrepreneurs – usually coined ethnic
entrepreneurs − play a prominent role
 Presents findings on the efficiency profiles of ethnic
entrepreneurs in Dutch cities.
 Argues that the se entrepreneurs appear to move increasingly to
high-skilled segments of urban business life, offering a boost to
the local economy.
8. Smart Cities in Perspective − A Comparative European Study by Means
of Self-Organizing Maps by Karima Kourtit, Peter Nijkamp and Daniel
Arribas
 Presents a study on the relative differences among smart cities by
analysing a multi-dimensional set of urban attributes related to smart
cities
 Employs an analytical tool set which is based on self-organising
mapping analysis
 Points the idea that some cities (actually most of them) have
'converged', that is, they have become more similar over the
observation period ,while others have become a bit of outliers in
positions where they were not found before

41.  This special issue offers new horizons on the innovation and
knowledge drivers, the functioning and the positioning of
smart cities
 There is a need for a conceptual clarity of smart cities, that is
evidence-based and appropriate for empirical
measurement and comparison
 For strategic policy support, an evidence-based monitoring
and benchmarking system for smart cities has to be
designed (urban compass)
 It is also evident that strategic urban policy should exploit
the knowledge-intensive and creative potential of smart
cities: knowledge creation, access and use are critical
parameters for the future of our cities