Making Competitive Creative Knowledge Cities: Urban Challenges Capital p Criativo numa
Regi達o Capital Lisbon 6 December 2011
Sako Musterd Urban Geography University of Amsterdam Accommodating creative knowledge
Source: Buiilt Environmentt 2004, 30 (3)
The Making of the C Creative ti Knowledge City
O tline Outline • • • • •
ACRE project Definitions Theory Empirical p Evidence ((and methodology) gy) Conclusions
ACRE – Accommodating Creative g – Competitiveness p of Amsterdam knowledge Barcelona European Metropolitan Regions Birmingham • • • •
EU 6th framework p programme g October 2006-2010 4.5 Million Euro 13 urban b regions i / partners t
Budapest B d t Dublin H l i ki Helsinki Leipzig Milan Munich Poznan Riga Sofia Toulouse
ACRE project objecti objective e Objective: to learn more about the conditions that are important to the development of creative and knowledge intensive industries in various European urban regions
Creative industries Advertising, architecture, arts and antiques, a t ques, crafts, c a ts, design, des g , designer des g e fashion, as o , video, film, music, photography, visual and performing arts, arts publishing publishing, computer games, software and electronic publishing, radio di and d TV
Creative industries Advertising, architecture, arts and antiques, a t ques, crafts, c a ts, design, des g , designer des g e fashion, as o , video, film, music, photography, visual and performing arts, arts publishing publishing, computer games, software and electronic publishing, radio di and d TV
Knowledge intensive industries Law (legal sector, accounting, bookkeeping, auditing, etc), financial sector, t R&D, R&D ICT ICT, hi higher h education d ti
Knowledge intensive industries Law (legal sector, accounting, bookkeeping, auditing, etc), financial sector, t R&D, R&D ICT, ICT higher hi h education d ti
Theoretical framework: two steps • Deep structural factors and pathways • Contemporary p y factors: hard (classic) conditions clustering l t i networks soft conditions
Three target groups Settlement considerations of • Managers g • High-skilled employees • High-skilled Hi h kill d ttransnational ti l migrants i t
Theoretical framework: five interrelated theories • • • • •
Path dependence theory ‘Classic’ location theoryy ((hard conditions)) Cluster theory Individual trajectories and network theory Soft conditions theory (‘talent’) ( talent )
Path dependence theory; deep structural factors • The question whether the urban region has had a key political or economic decisionmaking function • Position due to the development of the European city system • The impact of the industrial revolution on the urban region Boschma, Martin Boschma Martin, Sunley, Sunley Malecki Malecki, Lees Lees, Hohenberg, Camagni, Capello
‘Classic’ Classic location theory ((hard a d conditions) co d t o s) • • • • •
Labour and skills Capital availability ( ) Institutional context (subsidies) Regulations (tax regime) Infrastructure (airports (airports, telecommunication, telecommunication universities) • Accessibility • Availability of good quality locations and spaces Sassen, Taylor, Glaeser
Cluster theory • Geographic g p concentrations at a certain scale of interconnected industries and institutions, public and private services, context, agglomeration l ti economies i • Shaped over time (path dependence) and profit fi from f available il bl infrastructure, i f universities, etc. (also see hard conditions) Porter, Wu, Saxenian, Bathelt
Individual trajectories and network theory • • • • •
Personal ties (also transnational) Local social relations Individual trajectories Organisational affiliations Competition and cooperation Grabher Beccatini Grabher, Beccatini, Ganne
Soft conditions theory (conditions (co d t o s for o attracting att act g ‘talent’) ta e t ) • • • • • • • •
Urban amenities Quality of life g quality q y public p space p High Urban atmospheres (‘look and feel’) Tolerance Openness Diversity Housing market (availability, affordability) Florida, Landry, T. Clark
Empirical evidence
Urban region
Quasi hypothetical ranking of urban regions on deep p structural positions
Amsterdam Barcelona Dublin Munich Helsinki Budapest Milan Riga Leipzig Sofia Toulouse Poznan Birmingham
Known as established international political and economic decision making centre
Internationally known as strong historical centre for education, government and commerce
Known as strong high hightech centre or early service centre
Manufacturing industry was never dominant
Confronting theoretical positions based on deep structural positions with employment and GDP per region g information p 13 E European metropolitan t lit regions i (data for 2000-2006)
City regions Theoretical top (structural positions)
Employment in knowledge GDP per capita in in creative intensive the region industries (%) industries (%)
Amsterdam
+++
8
18
High (50,000+)
Barcelona
+++
12
10
Medium (25 (25-50,000) 50 000)
Dublin
+++
11
10
High
Munich
+++
8
21
Hi h High
Helsinki
+++
13
18
Medium
B d Budapest t
++
13
16
L Low (< 25 25,000) 000)
Milan
++
14
17
Medium
Ri Riga
++
6
23
L Low
Leipzig
++
9
16
Low
S fi Sofia
+
8
19
L Low
Toulouse
+
6
16
Medium
Poznan
+
7
11
Low
Birmingham +
6
19
Medium
City regions Theoretical top (structural positions)
Employment in knowledge GDP per capita in in creative intensive the region industries (%) industries (%)
Amsterdam
+++
8
18
High (50,000+)
Barcelona
+++
12
10
Medium (25 (25-50,000) 50 000)
Dublin
+++
11
10
High
Munich
+++
8
21
Hi h High
Helsinki
+++
13
18
Medium
B d Budapest t
++
13
16
L Low (< 25 25,000) 000)
Milan
++
14
17
Medium
Ri Riga
++
6
23
L Low
Leipzig
+
9
16
Low
S fi Sofia
+
8
19
L Low
Toulouse
+
6
16
Medium
Poznan
+
7
11
Low
Birmingham +
6
19
Medium
Some impact of deep structural conditions; other variance may be due to: contemporary p y ‘hard’ and/or cluster conditions … or to t contemporary t ‘soft’ ‘ ft’ conditions diti … or to ‘network’ network conditions and individual trajectories …
Integrated Methodology Methodolog • • • • • • •
‘Comparative’ ‘C ti ’ ‘Similar’ sectors ‘Similar’ target groups ‘Si il ’ questionnaires ‘Similar’ i i ((common d design) i ) ‘Similar’ Similar item lists Systematic approach (more robust results) Including different theoretical perspectives (path p clustering, g classic conditions, soft dependence, conditions, networks)
Three field work ork tests • Survey among high-skilled employees (n is 2500) • In depth interviews among managers (n is 300) • In-depth interviews among transnational migrants (n is 300)
Some empirical results based on the ACRE large-scale surveys among high-skilled hi h kill d employees, l managers and transnational managers, migrants
High-skilled g employees; p y ; Concepts p Networks b born iin region i family lives here studied in city proximity to friends
Hard conditions moved because of my job moved because of partner's job good employment opportunities hi h wages higher size of city good transport links presence of good universities
Soft conditions weather/climate proximity to natural environment housing affordability housing availability housing quality safe for children open to different people open minded and tolerant gay/lesbian friendly language overall friendliness diversity of leisure & entertainment cultural diversity diversity of built environment
High-skilled employees ranking indicators as most important, classified as indicators for networks networks, hard hard, and soft factors Networks
Soft Hard conditions conditions
Total percentage
N
Amsterdam
38
35
26
100
221
Barcelona
62
27
11
100
200
Birmingham
57
38
5
100
165
Budapest
71
24
5
100
197
Helsinki
51
39
10
100
191
Leipzig
43
50
8
100
159
Munich
30
60
10
100
178
Poznan
74
23
3
100
155
g Riga
80
17
4
100
132
Sofia
91
10
100
200
Toulouse
47
42
10
100
191
Milan
64
32
4
100
183
Dublin
57
42
1
100
201
T t l Total
58
34
8
100
2373
Special categories
Networks
age <35
59
36
income <1000
70
self employed
Hard Soft conditions conditions
%
Total
6
100
1239
24
6
100
339
58
31
11
100
542
less than 1 yr in the city
21
76
3
100
90
more than 1 yr in the city
60
32
8
100
2283
fi firm size i < 10
60
30
10
100
659
All survey
58
34
8
100
2373
C rrent debates highlighted Current Employment Opportunities moved because of my job moved because of partner's job good employment opportunities
Diversity diversity of leisure & entertainment cultural diversity
Openness p and Tolerance open to different people open p minded and tolerant gay/lesbian friendly
Personal Networks born in region family lives here studied in city proximity to friends
Relative share of respondents that ranked indicators as among the th four f mostt important i t t from f a list li t off 26 indicators, i di t assembled in specific dimensions, per urban region 100%
personal networks diversityy openness and tolerance employment opportunities Total T
Du ublin
Milan M
Toulo ouse
Sofia S
Riga R
Pozznan
Mun nich
Leip pzig
Helssinki
Budap pest
Birmingh ham
Barcellona
Amsterd dam
0%
Managers • • • •
Infrastructure L b Labour pooll Universities Networks (personal, business) – Less for consultants (for them: accessibility) – More for film p production,, video,, media,, webdesign, internet and games activities – More for smaller firms; less for larger firms
Transnational migrants â&#x20AC;˘ Employment opportunities â&#x20AC;˘ Personal trajectories and networks â&#x20AC;˘ Difference between creative industries (more networks) and knowledge intensive industries (more inner firm related)
Preliminary conclusions • Deep structural and contemporary factors are key to understand ci and ki development • Context Context-specific specific pathways and historically grown place specific characteristics are important • Personal trajectories and networks networks, and job opportunities are key contemporary variables • Classic ‘hard’ conditions remain essential essential: infrastructure (telecommunication, airport), universities i iti
Additional considerations â&#x20AC;˘ Urban amenities, high-quality urban space, urban atmospheres, atmospheres and proper residential accommodation are not important to attract creative knowledge g workers;; but may y be important to retain them p clusters,, also in the existing g city, y, â&#x20AC;˘ Specialised may be relevant (not fully researched in ACRE): spatial patterns of creative industry i Amsterdam in A d suggest importance i off specific urban milieus
Urban Orientation of employees in Creative Business Services (brown) and in Law Firms (blue) in Amsterdam 2005 CBS in region: 2% of employment CBS in concentrations : 22% (avg) Law in region: 4% of employment Law in concentrations : 44% (avg)
Urban Orientation of employees in the Arts Sector in Amsterdam 2005 Arts in region: 1% of employment Arts in concentrations 2005: 31% (avg)
Urban Orientation of the Arts Sector in Amsterdam 1995 (blue), 2005 (brown) Arts in region: 1% of employment Arts in concentrations 2005: 31% (avg) Arts in concentrations 1995: 30% (avg)
Spatial Association between the Arts Sector and Old Urban Structures brown 2005 arts, blue 2008 old structures Arts in region: 1% of employment Arts in concentrations: 31% Old structures: 80% b built il b before f 1920
Lessons for Urban Restructuring • Historically grown contexts are conditioning hard conditions are still relevant; • Classic ‘hard’ invest in infrastructure (telecommunication, airport), a po t), universities u e s t es • Urban amenities, high-quality urban space, urban atmospheres, and proper residential accommodation may be important to retain creative knowledge g workers • Specialised clusters, also in the existing city, seem to be relevant to nurse creative and knowledge intensive industries
PPCC-T instead of 3 T’s • • • •
Pathways P th Personal Networks Classic conditions Clusters Tailored Policies
Sako Musterd - Urban Geographies - University of Amsterdam
http://acre.socsci.uva.nl/
Critical comments (on Florida) • Storper and Manville (2006): not skills, but fi firms (agglomeration ( l ti economies) i )d drive i g growth • Peck (2005): Florida is merely a neolib l h liberal hype • Hall (2004): Building innovative cities takes time • Markussen (2006); Pratt (2005); etc.
Status of the city National/ regional capital + important decision making
Considered as a world city of any rank
Economic profile Competitive spirit (cities with a 'drive')
Diversified economic profile
No negative industrial heritage or image
Historical/cultural background Powerful high-tech clusters
PathPath ways with periods of glory
Important internation al function in the past
W.Europe Amsterdam
3
3
2
3
3
2
3
3
Barcelona
3
2
3
3
2
2
3
3
Birmingham
1
2
2
2
1
1
2
1
Helsinki
3
2
2
2
3
3
1
1
Leipzig
1
2
1
2
2
1
3
2
Munich
3
2
3
3
3
3
3
2
Toulouse
1
1
1
2
3
3
1
1
Milan
2
3
2
3
3
1
3
3
Dublin
3
2
2
3
2
1
2
2
Budapest
3
2
3
3
2
1
3
3
Poznan
1
1
3
3
1
1
1
1
Riga
3
2
3
3
1
1
2
2
Sofia
3
2
3
3
1
1
1
1
E.Europe
3 – strong 2 – medium 1 – relatively weak or no score
Some impact of deep structural conditions; other variance may be due to contemporary ‘hard’ and/or cluster conditions … Estimated positions on these conditions (ranked) • Milan, Mil M Munich, i h A Amsterdam t d • Helsinki,, Barcelona,, Dublin,, Leipzig p g • Birmingham, Budapest, Riga, Toulouse • Poznan, P S Sofia fi
… or to contemporary ‘soft soft conditions … conditions’ Estimated strong position on ‘soft’ conditions • W.Europa: Amsterdam, Munich, Barcelona • E. Europa: Budapest, Leipzig, Riga
… or to t ‘network’ ‘ t k’ conditions diti and d individual trajectories …
?