This presentation was featured at the 11th OECD Rural Development Conference held on 9-12 April 2018 in Edinburgh, Scotland (UK). More information: www.oecd.org/rural/rural-development-conference/
Antisemitism Awareness Act: pénaliser la critique de l'Etat d'Israël
Timothy Wojan - A data-driven Contrarian View of Smart Specialisation
1. A Data-Driven Contrarian View
of Smart Specialisation
Timothy R. Wojan
Economic Research Service/USDA
Panel on Smart Specialisation and Access to Markets
11th OECD Rural Development Conference: Enhancing
Rural Innovation
Edinburgh, Scotland, 11 April, 2018
The views expressed are those of the authors and should not be attributed to
the Economic Research Service or USDA
2. The Logic of Smart Specialisation
Vulnerable to
Confirmation Bias
• If regional science starts from the premise that
“place matters” then there is a lot to like about
smart specialization
• STEM workers, R&D labs, the infrastructure for
formal innovation systems are highly
concentrated spatially
• A cynical interpretation of smart
specialistation: the linear model of innovation
repackaged to take direction from
entrepreneurial explorations
3. Opportunities of Spatially
Distributed Innovation
Imaginariums
• Resources for atomized invention and
innovation expanding at a rapid rate (von
Hippel)
• Global digitalization and new social media
platforms are expanding ability to target
niche markets and develop global networks
(Manyika and Lund 2016)
• Innovation tournaments demonstrate that
creative genius randomly distributed
4. Do Highly Innovative Rural Firms in
U.S. fit Smart Spec. Profile?
• Establishments in Rural Establishment
Innovation Survey that are classified as both
design-integrated and pursuing far-ranging
innovation initiatives (4.3% of rural sample vs.
11.3% of urban)
• Expectation that these establishments more
likely to be:
– element of triple helix complemented by
government and university
– beneficiaries of rich local information flows
5. How impressive are these highly
innovative establishments?
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Increased variety goods/services
Increased market share
Begun exporting goods/services
Respond to customer needs quicker
More flexible production/service provision
Greater capacity for production/service provision
Reduced labor costs per unit
Reduced materials or energy per unit
Improved worker satisfaction
How Impressive are these Highly Innovative Establishments?Self-
Reported Performance,Past 3Years
Rest of Sample Highly Innovative Establishments
Source: 2014 Rural Establishment Innovation Survey
6. Triple helix found in < 25% of
highly innovative establishments
• Is university and any level of government very
active in promoting business in your
community?
23.97
16.55
76.03
83.45
0 10 20 30 40 50 60 70 80 90
Highly Innovative Establishments
Rest of Sample
No Yes
Source: 2014 Rural Establishment Innovation Survey
7. Knowledge management in highly
innovative establishments
• Dearth of empirical data makes localized
knowledge flows the default assumption
• Community Innovation Survey (2014) only
asks about international collaboration
• Rural Establishment Innovation Survey (2014)
asks:
– What are the most valuable sources of
information?
– Where are these sources located?
8. Majority of Most Valuable
Information Comes from Some
Distance
Source
in
community
w/in
reasonable
drive
beyond
reasonable
drive
Suppliers HIE 13.82 39.77 46.41
RoS 13.32 48.46 38.22
Customers HIE 18.21 24.9 56.9
RoS 50.22 33.1 16.68
Contacts Own Industry HIE 11.04 34.87 54.09
RoS 16.32 52.03 31.66
Contacts Other Industries HIE 9.82 31.65 58.53
RoS 24.3 45.16 30.54
Source: 2014 Rural Establishment Innovation Survey
9. A Contrarian View is not a
Refutation
• Simple analysis of wholly different population
is not meant to challenge smart specialisation
• But the data from the rural US are consistent
with a different geography of innovation
• The long-running demand for better data to
assess smart specialisation
• Intent to open up debate for case studies:
– To what extent do cases comport with ss
predictions?
– Are unexpected findings supported by a
contrarian view?