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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
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
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
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
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
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
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?
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
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?
Chapter 1:
Opportunities
and
Challenges of
Spatially
Distributed
Innovation
Imaginariums

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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?