Innovation

1

• Innovation the Science BaseEvidence from the
  UK CIS-3
• Work in Progress!
• Bruce Tether Peter SwannCRIC and MBS,
  University of Manchester

2

• Overview

• Motivation
• Criticism Science Base Could do Better to
  Support Innovation
• Charles Clarke Medieval Truth Seeking is
  insufficient justification
• Lambert Review - Treasury (and DTI) sponsored
• Exploration of CIS-3 Data
• Direct Links (Source of Information
  Collaborations with Industry)
• Indirect Links (role of graduates intermediate
  firms)
• Factors Impeding Innovation
• Conclusions Implications

3

• UK Version of the Community Innovation Survey

• Undertaken in 2001
• Relates to Innovation activities in 1998 - 2000
  period.
• Identical questionnaire used for manufacturing
  and services
• Enterprises with 10 employees surveyed
• Excludes public services, retail, hotels,
  catering personal services
• 8,172 responses - 42 response rate
• 4,567 responses from Production and
  Construction
• 3,605 responses from Services and Distribution
• Overall (when adjusted), 47 innovation active,
  although
• Only 18 were product innovators 16 were
  process innovators

4

• Direct Importance As Source of Information

• Overall Unweighted (of Enterprises with
  Innovative Activities)
• Production Activities 34 use Universities for
  Info. (2 High Impt)
• Services Activities 24 use Universities for
  Info. (2 High Impt)
• Production Activities 23 use Govt Res Orgs for
  Info. (1 High Impt)
• Services Activities 19 use Govt Res Orgs for
  Info. (1 High Impt)
• Production Activities 39 use Public Science
  Base (3 High Impt)
• Services Activities 29 use Public Science Base
  (2 High Impt)
• C.f. Unweighted (of Enterprises with Innovative
  Activities)
• Within enterprise, suppliers customers 75
  used, 20 Hi-Impt
• Private Sources of expertise 60 used
  Services - 9 High Importance Production - 5
  High Importance

5

• Direct Importance As Source of Information

• Ordinal Logistic Regression - Production
  Activities
• Positive relationship with Size also New Firms
  more likely to use.
• Firms engaged in International Markets ()
• Firms engaged in RD, Long-term Innovation
  Activities ()
• Firms engaged in Product Innovation Imitation
  ()
• Firms that introduced innovations developed by
  others (-)
• Firms engaged in Process Innovation and Imitation
  ()
• Firms engaged in following sectors Hi-Tec.
  Instruments, Transport Equip Electrical Equipt
  Chemicals Metals Utilities Construction ()
• Pseudo R2 0.2
• Suggests that Science-base links are more impt
  than headline implies

6

• Direct Importance As Source of Information

• Ordinal Logistic Regression - Service Activities
• (Weaker) Positive relationship with Size New
  firms effect also weaker
• No strong relationship with scale of market
  activities
• Firms engaged in RD, Long-term Innovation
  Activities ()
• Firms engaged in Product Imitation (), weaker
  re. Innovation
• Firms engaged in Process Innovation (), but not
  Imitation ()
• c.f. Wholesale, firms engaged in following
  sectors more likely Architecture Eng. Cons
  RD Tech. Testing (N.B., not CompSers)
• c.f. Wholesale, firms engaged in following
  sectors less likelyBanking Finance Goods
  Transportation - both quite weak effects
• Pseudo R2 0.2 Also suggests assoc. with
  greater innovation effort.

7

• Direct Importance As Collaborative Partner

• Overall (for Enterprises with Innovative
  Activities)
• Production 9 had Partnerships for Innovation
  with Universities
• Services 5 had Partnerships for Innovation with
  Universities
• Production 3 had Partnerships for Innov. with
  Govt Res. Orgs.
• Services 2 had Partnerships for Innov. with
  Govt Research Orgs
• Production 10 had Partnerships for Innov. with
  the Science Base
• Services 6 had Partnerships for Innovation with
  the Science Base
• C.f., Production Suppliers (13), Customers
  (12) Private Sources of Expertise (10)
• C.f., Services Suppliers (12), Customers (9)
  Private Sources of Expertise (8)

8

• Direct Importance As Collaboration Partner

• Binary Logistic Regression - Production
  Activities
• Positive relationship with Size weak evidence
  New Firms more likely.
• Firms engaged in International Markets ()
• Firms engaged in (Cont.) RD, Long-term
  Innovation Activities ()
• Firms engaged in (Own) Product Innovation
  Imitation ()
• Firms engaged in Process Innovation (not
  Imitation) ()
• Firms engaged in following sectors
  Instrumentation, Chemicals Metals Electrical
  Utilities Construction ()
• Pseudo R2 0.25
• Suggests that Science-base links more are more
  important than headline implies (although not a
  linear model)

9

• Direct Importance As Collaboration Partner

• Binary Logistic Regression - Service Activities
• No significant relationship with Size New Firms
  not more likely.
• Firms engaged in International Markets (, but
  weak)
• Firms engaged in Product Innovation Imitation
  ()
• Firms engaged in (Cont.) RD, Long-term
  Innovation Activities ()
• Firms engaged in Process Imitation (, but weak,
  not innovation)
• Firms engaged in following sectors RD
  Technical Testing (, weaker in Architecture and
  Eng. Consulting), Banking (-, weaker with
  Professional Services)
• Pseudo R2 0.33
• Suggests that Science-base links more impt than
  headline implies

10

• Direct Importance Summary

• Rarely Important Source of Information for
  Innovation
• Although unadjusted 39 of Production and 29
  of Service enterprises used Science Base for
  Information (Surprisingly High?)
• But of High Importance to only 3 and 2
  respectively.
• Other sources, esp. within Enterprise, Custs
  Suppliers more Impt.
• Very Rarely Engaged as Collaborative Partner for
  Innov.
• Except amongst RD and Technical Testing
  Enterprises (45)
• However More Important than may Appear
• Interaction associated with Firms competing
  Internationally
• those that engaged in RD and introduced
  innovations

11

• Evidence of Importance of Own Absorptive Capacity
• Both Production and Services engaged in RD
  (continuously) more likely to use Science Base as
  Source of Info Collaborative Partner
• Services are less likely to use than Production
• Why? Universities less geared to service
  activities
• Services less traded, competition is
  local/national not international
• Different type of knowledge more often provided
  by consultants(including academics working as
  consultants)
• Problems of IPR and reaching agreements in
  services?
• Emergence of knowledge transfer service firms
  (?)
• IT Services have surprisingly little connection
• Manuf. - Gtr connection in Medium than High
  Technology

12

• Indirect Importance Introduction

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• Indirect Importance Provision of Graduates

• Graduate Employment
• Very High in some activities - esp. Computer
  Technical Services
• Very Low in others activities - esp. Transport
  Services, Construction
• Employment of Graduates
• After controlling for size, age, market scale and
  sector of activity
• Increases probability of both Product and Process
  Innovation
• True in Both Production and Service Activities
• True of All Graduates and Sci. Eng. Graduates
  in particular
• Impact increases if Proportion of Graduates gt
  Sector Average

15

• Indirect Importance Employment of Graduates

• Employment of Graduates (continued)
• Production Activities - Employment of Graduates
  increases use of Universities and Science Base as
  Source of Info. for Innovation
• Firms with gt Ave Proportion of Graduates even
  more likely to use.
• Service Activities - Employment of Graduates at
  higher than median proportion for sector
  increases use of universities science base
• Collaboration arrangements - weaker evidence that
  firms with high proportion of graduates for
  sector are more likely to collaborate with
  universities and the science base.
• Overall, suggests that employment of graduates
  raises firms absorptive capacity to learn from
  Public Science

16

• Indirect Importance Diffusion of Knowledge

• Enterprises Only Acknowledge Direct Sources
• Homely example - Retailers identified, not
  Manufacturers
• However, Several Indirect Links
• Acquired RD RD enterprises act as translators
  from Sci-Base
• Competitors use of Science Base diffusion of
  info to industry
• Suppliers Science Base knowledge into Embodied
  Form
• Standards / Regulations informed by research
  from Science Base
• Not Advocating a Linear Model (innovators draw on
  multiple sources)
• But Indirect Contributions are Easily Overlooked
• And Very Difficult to Measure!

17

• Factors Inhibiting Innovation

• Firstly, Lack of Ambition / Willingness to take
  Risks
• Production Activities Only 38 successfully
  innovated
• Service Activities Only 27 successfully
  innovated
• But 38 of Production and 46 of Service
  Enterprises declaredNo Need to Innovate due to
  Market Conditions
• Only 11 of Production 7 of Services Impeded
  Non Innovators
• Remainder were Incomplete Innovators, or not
  enough information

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• Impeded Non-Innovators

• Impeded Non-Innovators Factors Impeding
• Production 66 cite lack of Information on
  Technology as a factor
• but only 11 declare this to be a factor of High
  Importance
• Services 58 cite lack of Information on
  Technology as a factor
• but only 7 identify this as being of High
  Importance
• Overall, Access to Technology is amongst Least
  Significant Barriers
• Financial Aspects (Direct Cost of Innovation
  Cost of Finance) more important, as is the lack
  of Willingness to Take Risks
• Access to qualified personnel intermediate
  problem (but more likely to be cited by
  non-innovators than by innovators)

20

• Conclusions from CIS-3 Analysis

• Direct Contribution of Science Base to Innovation
• Usually Small, higher in Production than in
  ServicesException RD Technical Testing
  (in business of tech transfer !)
• Surprisingly low in some sector - e.g., Computer
  Services
• Higher amongst International Competitors and
  Successful Innovators
• More Significant than First Appears?
• Indirect Contribution (Difficult to Measure,
  but.)
• Considerably Gtr Impact of Graduates on
  Innovation Performance
• Access to Technology not Major Impediment to
  Innov.
• C.f Lack of Ambition, Lack of Willingness to take
  Risks

21

• Policy Implications

• Consider Costs Benefits of Strengthening Direct
  Links
• Technology Transfer threatens Openness of Science
  (David/Florida)
• Are Opportunity Costs being considered? (and IPR
  issues?)
• Model Universities at the core of knowledge
  based clusters Replicating US approach of
  1980s - that went too far (Florida)
• Consider deeper reasons why Industry doesnt use
  the Science Base
• Lack of Willingness to Engage in Innovation but
  also
• Evidence that Under-funding has Reduced
  Attractiveness
• e.g., UK University Computer Science
• Strong in Theory, because it is Cheap.
  Industry not Interested

22

• Wider Context

• UK about to embark on radical reform of
  Universities?
• Context - 1992 Polytechnics become Universities
• Research Assessment Exercises - emphasis on
  Research
• Currently - 25 of Universities do 75 of
  Research
• Increasingly realisation that one size cant fit
  all.
• Three types of University (?) Not better or
  worse, but different!
• Type 1 - Research Based (_at_6) - Oxford, Cambridge,
  Imperial, UCL(fight for last 1 or 2 places -
  motivates Manchesters merger) ?
• Type 2 - Technology Transfer ( Regional
  Development Role) ?
• Type 3 - Teaching only (mainly former
  Polytechnics) ?

23

• Wider Context

• Richard Lambert, evidence to the Education Select
  Committee
• my prejudice is that there are things that
  research-based universities should not be doing
  for industry. I do not think that it is the job
  of, say, Imperial to be the product development
  fire-fighter for a manufacturing company that is
  having problems with a product, it is not their
  job to sort it out, it is their job to get new
  knowledge.
• Not for the Research Based, but for the second
  tier?
• e.g., Newcastle, long advocated a technology
  transfer / regional devt role for the
  university in the community.

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• Knowledge Transfer Whose job is it anyway?