This document summarizes research on skills, management practices, and productivity in small and medium enterprises (SMEs). The main points are: 1. The research examines the links between managerial skills, practices adopted by SMEs, and productivity using survey and longitudinal data. It finds that higher entrepreneurial skills are associated with more structured managerial practices, and adopting more practices leads to higher productivity. 2. Key results show entrepreneurial skills, leadership skills, and organizational skills are positively correlated with productivity. Adopting additional human resource practices is also linked to around 2% higher productivity after 3 years. 3. The implications are that both skills development and coaching to help firms adopt practices are needed to

1. @ERC_UK
ERC Research Showcase
29 January 2018
RSA

2. Bo Peng, Kevin Mole
and Stephen Roper
Skills, management
practices and
productivity in SMEs
Acknowledgement: We are grateful to Prof
James Hayton (Warwick Business School) for
providing the data on which this analysis is
based

3. Opening remarks
• L&M practices and quality have received significant attention
recently. In the Industrial Strategy we find the assertion that
‘management skills could account for a quarter of the productivity
gap between the UK and US’ (p. 169).
• Skills alone cannot however drive productivity.
• It is only when skills drive practical actions- strategy or practices -
that they can drive performance. Un-utilised or under-utilised skills
will yield no performance benefits.
• Here, we match survey data on management skills and practices in
a large group of SMEs with longitudinal data on productivity and
examine the causal links between skills, practices and productivity

4. Skills, practices &
performance
• In the identification of firm growth Edith Penrose
suggested managers have ‘opportunity sets’ where they
identify opportunities to grow, as a managerial constraint
• Evidence links managerial skills indirectly to firm
performance often through their impact on goal setting,
and the communication of vision – both of which might
be considered management practices
• Standard economics suggests that more efficient
businesses will grow (e.g. Lucas)
• Extensive evidence links HR practices to performance
often as a bundle of high performance work practices

5. Hypotheses
• H1: Higher entrepreneurial skill levels will be
associated with the adoption of a more
structured managerial practices.
• H2: Adoption of more structured managerial
practices will lead to higher productivity.
Skills Practices Productivity

6. Data sources
• Skills, practices
• Study undertaken by James Hayton (ERC/WBS) in 2014 (and published
in BEIS Research Paper series
• Aim to capture generic skills and practices important across all sectors
• IDBR based telephone survey of firms with 5-250 employees
conducted in 2014, independent companies only
• Focus here only on firms with a solo lead manager rather than a team
management structure – around 1700 firms
• Dimensions of skills: Leadership, Entrepreneurship, Organisational,
Technical
• Dimensions of strategy and practices: Centralised, formalised,
responsive and HRM
• Productivity
• Business
Structures
Database for
2017
• Measured as
turnover per
employee
• Matched
with L&M
survey data
using
reference
numbers

7. Skills measures
Leadership (0.808)
• Organising and motivating people
• Delegation
• Supervise and lead
Entrepreneurial (0.734)
• Accurately perceive gaps
• Identifying market opportunities
• Seizing market opportunities
• Identifying demands
Organisational (0.758)
• Allocating limited resources
• Organising and co-ordinating tasks
• Managing effective working
Technical (0.744)
• Technical or functional expertise
• Product or service development

8. Strategy and practices
Centralised Strategy (0.561)
• Strategy set by the CEO
• Vision set by the CEO
• Strategy implementation led by CEO
Formalised Strategy (0.782)
• Formalised planning process
• Strategic plan
• Mission statement
Responsive Strategy (0.781)
• Competitor analysis
• Collaborative strategy formation
• Planning involves all staff
Human Resource Mment (𝜶𝜶 =0.670)
• Training
• Performance appraisal
• Recruitment practices
• Incentive related payments

9. Key results (n=1,774)
(significant relationships)
Productivity
2017
Entrepreneur
Skills
Leadership
Skills
Organisational
Skills
Technical
Skills
Centralised
Strategy
HR Practices
Responsive
Strategy
Formalised
Strategy
Adding an additional
HR practice adds
around 2 per cent to
productivity after 3
years

10. Implications
• Strong support for Hypothesis 1 and in terms of HR Practices
Hypothesis 2
• Skills matter as they are strongly associated with practices
• Practices matter as they lead to productivity growth. Same
outcomes for small (5-49) and medium sized (50-249) firms
• In policy terms this suggests complementarity between training to
build skills and mentoring/coaching to help firms develop practices.
• Both may be necessary to maximise the productivity gains

11. Next steps
• To test the mediation between the skills and
the practices i.e. do some skills in year 1
directly link to productivity in year 1+3
• To test the same relationships hold for
different types of firms such as family firms
• To test whether similar or stronger
relationships hold for more experienced
managers

12. And the small print …
• The statistical data used here is from the Office of
National Statistics (ONS) and is Crown copyright
and reproduced with the permission of the
controller of HMSO and Queens Printer for
Scotland. The use of the ONS statistical data in
this work does not imply the endorsement of the
ONS in relation to the interpretation or analysis
of the statistical data. The analysis upon which
this paper is based uses research datasets which
may not exactly reproduce National Statistics
aggregates.

13. Areti Gkypali, Enrico Vanino,
Stephen Roper and Nola
Hewitt-Dundas
Assessing the spillovers
from publicly funded
R&D projects – some
initial results

14. Starting points...
• Spillovers from R&D and innovation activity are of two main sorts
(Griliches 1992, 1979):
– Rent spillovers arise when quality improvements by a supplier are not
fully translated into higher prices for the buyer(s). Productivity gains
are then recorded in a different firm or industry than the one that
generated the productivity gains in the first place.
– Pure knowledge spillovers are benefits of innovative activities of one
firm that accrue to another without any market transactions.
• Spillovers are important as they define the difference between the private
and social value of R&D and innovation and provide the rationale for
public intervention (Arrow, 1962). The stronger and more positive
spillovers the stronger the rationale for public intervention.

15. Starting points…
• Here, we are going to focus on local knowledge spillovers and their innovation
impact as:
– ‘local knowledge is … a semi-public good that is spatially bounded … local
knowledge exchange is prompt or spontaneous because local firms are
assumed to be more willing to share knowledge and exchange ideas with
other local actors as a result of shared norms, values, and other formal and
informal institutions that hold down misunderstanding and opportunism’ (He
and Wong, 2012, p. 542).
• So our research question is:
Do Research Council funded R&D and innovation projects generate local
knowledge spillovers which raise levels of innovation in their locality?
• The answer is yes. But its not quite as simple as you might think!

16. Spillovers – one way firms get
knowledge to drive innovation…
Innovation
Outcomes
Interactive
Learning
Spillovers
Non-interactive
Learning
Knowledge Context
Encoding
Capacity
Innovation
Ambition
Spatial Sectoral
Network
Learning
mechanisms
ACAP
Source: Roper and Love (2017)
‘Knowledge context, learning and
innovation: an integrating
framework’, Industry and
Innovation, forthcoming.

17. Two other things you need to
know…
Process and output spillovers
• Spillovers may result from the
process of innovating or the outputs
of the innovation process
• Process spillovers are pure
knowledge spillovers resulting from
knowledge diffusion – positive
• Output spillovers occur through
supply-chain (+ve) or local
competition (-ve) effects
• Research Council projects may
generate both types of spillover so
their sign is ambiguous ex ante
Absorptive capacity
• Firms have very different internal
resources in terms of R&D, skills and
innovation capacity
• Smaller firms are typically thought of
as having less absorptive capacity
than larger firms
• Smaller firms may therefore be less
able to benefit from spillovers
• Smaller firms may benefit less from
process spillovers and be more
vulnerable to local competition
effects.

18. Our empirical focus here… from
spillovers to innovation
Innovation
Outcomes
Interactive
Learning
Spillovers
Non-interactive
Learning
Knowledge Context
Encoding
Capacity
Innovation
Ambition
Spatial Sectoral
Network
Learning
mechanisms
ACAP
Source: Roper and Love (2017)
‘Knowledge context, learning and
innovation: an integrating
framework’, Industry and
Innovation, forthcoming.

19. Data and methods
Augmented Innovation Production Function (AIPF)
𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝑛𝑛𝑛𝑛𝑛𝑛,𝑛𝑛𝑛𝑛𝑛𝑛 = 𝑓𝑓 𝐼𝐼𝐼𝐼𝐼𝐼. 𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼 𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼, 𝐻𝐻𝐻𝐻, 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶, 𝑅𝑅&𝐷𝐷 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠, 𝛽𝛽𝑥𝑥𝑖𝑖
UKIS  Waves 6-9
~12k obs
GtR*: Number of
grants received
at the LEP or
NUTS3 level
* Vanino E., Roper S. and Becker B., (2017). ‘Assessing the business performance effects of receiving publicly-funded science, research
and innovation grants’, ERC Research Paper 61

20. Key results (1): Size matters!
• Small firms: (consistently) negative effect of
publicly funded R&D spillovers on their
innovation performance (c. -3 %)
• Medium firms: (consistently) positive effect of
publicly funded R&D spillovers on their
innovation performance (c. 1 %)
• Large firms: (on the whole) positive effect of
publicly funded R&D spillovers on their
innovation performance (c. 0.5%)

21. Key results (2): Collaboration
matters!
• Positive effects of R&D spillovers for medium
and large firms which collaborate with at least
one partner for innovation (c. 1-1.5%)
• For non-collaborating large firms this effect
turns negative (c. -2%)

22. Key Results (3): Geography
matters!
• Firms located in London/South East:
consistently negative effect of R&D spillovers
on innovation performance, especially for
small firms (c. -2 to -6 %)
• Firms located in the rest of the UK: only
medium firms seem to benefit from publicly
funded R&D. (c. 2 %)

23. Next steps…
• Modelling has proved challenging here so requires more
robustness testing of results
– Other spillover indicators
– Different geographies
• Also want to test growth and productivity effects not just
effects on innovation. A different modelling exercise
• Industry spillovers may also be interesting alongside those
related to geography
• Working towards a research paper in March/April

24. Victor Ekpu and Mike Wright
E: mike.wright@imperial.ac.uk
Demand for growth
capital in peer-to-peer
business lending
markets

25. Introduction
• Debate about role of traditional finance providers
• High growth firms more likely to seek external
finance
– Unmet demand for growth capital limits firm growth
and constrain economic recovery (Rowlands, 2009; BIS,
2012; Fraser et al., 2015
• Role of alternative financiers in filling equity gaps
– Peer to peer (P2P) lending
• £62 million in 2012 to £1.49 billion in 2015
• Funding Circle lending boosted annual economic output by
£2.7 billion, measured via gross value added (CEBR, 2016).

26. Research Questions
• Know little about:
– Types of firms approaching peer-to-peer lending
– Types of capital sought (growth, working capital).
• What firm characteristics determine the
likelihood of obtaining growth capital from
peer-to-peer lending platforms?

27. • Demand for financing influenced by
– Firm age, firm size, sector (Mac an Bhaird, 2010)
• Second finance gap
– Supplement short term debt with larger amounts of long
term debt or external equity (Wilson, et al., 2018).
• Maturity
– Track record, Less growth ambition, earnings consolidation
• Beyond maturity Avoiding decline; reinvigoration of
business model
• High growth sectors
• Various studies show difficulties for these to raise
growth capital (eh Menzies, 2016).

28. • Data
• 39,268 loan-level observations
• Funding Circle loan book 2010 to 2017
• Variables
– DV: demand for growth capital compared to
working capital/asset finance loans (1,0)
• IVs:
– Age => stage (Robb, 2002; Mac an Bhaird, 2010)
– Sector
• Controls: risk band, region, loan year, macro

29. P2P Loans by Firm Growth Stage
Firm Stage Description Frequency Percent of Total
Young (1)* 1-4 years 5,003 12.74
Early Growth (2)* 5-11 years 3,827 9.75
Late Growth (3)* 12-19 years 9,002 22.92
Mature (4)* 20-29 years 2,483 6.32
Old (5)* 30-49 years 5,282 13.45
Very Old (6)* >=50 years 13,671 34.81
Total All firms 39,268 100.00

30. Dependent Variable:
Growth Capital
Model 2
Coefficient MEMS Coefficient
Constant .141***(0.01) n/a .138***(0.00)
Firm Stage
Young (base level) n/a n/a -.370***(0.00)
Early growth .236***(0.00) .059***(0.00) -.108***(0.01)
Late growth .071**(0.05) .018**(0.05) -.300***(0.00)
Mature -.082 (0.11) -.020 (0.11) -.366***(0.00)
Old .248***(0.00) .062***(0.00) -.185***(0.00)
Very old .318***(0.00) .079***(0.00) n/a
Industry
Property & construction -.659***(0.00) -.162***(0.00)
Manufacturing & engineering -.172***(0.00) -.043***(0.00)
Transport & automotive -.189***(0.00) -.047***(0.00)
IT & telecoms .187***(0.00) .046***(0.00) .415***(0.00)
Retail & wholesale .157***(0.00) .0392***(0.00) .389***(0.00)
Knowledge services .159***(0.00) .0397***(0.00) .356***(0.00)
Leisure & hospitality .167***(0.00) .042***(0.00) .417***(0.00)
Stage-Industry Interactions
Late growth*IT & telecoms .261***(0.00)
Young*Retail & wholesale .245***(0.00)
Old* Retail & wholesale .192**(0.02)
Old* Leisure & hospitality .371***(0.00)
Early growth* Knowledge services .201**(0.03)
Late growth* Knowledge services .205***(0.00)
Old* Knowledge services .243***(0.00)
Demand for Growth Capital in P2P Business Lending Markets
N 39,227 39,227
Log likelihood -26538.994 -26698.302
LR chi-square (df.) 1285.82***(19) 967.21***(23)

31. 0.00%
5.91%***
1.77%**
-2.00%
6.19%***
7.94%***
-4.00%
-2.00%
0.00%
2.00%
4.00%
6.00%
8.00%
10.00%
Young Early Growth Late Growth Mature Old Very Old
Demand for Growth Capital by
Firm Stage (Base Level = Young)
Marginal Effects at Means (MEMS) for Model 2

32. -16.20%***
-4.30%***
3.92%***
4.65%***
-4.74%***
3.98%*** 4.16%***
-20.00%
-15.00%
-10.00%
-5.00%
0.00%
5.00%
10.00%
Property &
Construction
Manufacturing &
Engineering
Retail & Wholesale IT & Telecoms Transport &
Automotive
Knowledge Services Leisure and
Hospitality
Demand for Growth Capital by
Firm Sector
Marginal Effects at Means (MEMS) for Model 2

33. Summary Findings
• Demand for growth capital higher in early stages
of growth than younger firms less than 5 years
old (second “finance gap”)
• Older firms above 30 years old, higher likelihood
of securing growth capital as age increases
• Demand for growth capital higher in certain
growth stages in the IT and telecoms industry,
retail and wholesale sectors, leisure and
hospitality and knowledge services industries.

34. Implications
• Promote peer-to-peer lending platforms as
complementary finance for early growth
stages/high growth potential firms and well-
established firms entering new markets/products.
– Older firms might have high growth ambitions to stay
ahead of competition & reduce decline risks
• Are they discouraged borrowers? And/Or unwilling to see
equity dilution?
• IT and telecoms industry, retail and wholesale
sectors, leisure and hospitality and professional
and business support industries
• But what about default?.......

35. • Default risk: borrower's risk rating, sector, loan
term, interest rate, purpose most influential
• Loans for growth/asset lower default than
working capital
1.43%
4.01%
5.28%
5.64%
4.31%
3.07%
5.56%
7.00% 6.93%
5.93%
0.00%
1.00%
2.00%
3.00%
4.00%
5.00%
6.00%
7.00%
8.00%
Asset Finance Growth Capital Working Capital Other Total
Default Ratio and NPL Ratio by Loan Purpose
Default Ratio NPL Ratio

36. Mark Hart and
Stephen Roper
Insights from ERC phase 2
SMEs, growth, innovation
and productivity –
What have we learnt?

37. Key finding from ERC Phase 2
(2016-17)
Stephen Roper and Mark Hart

38. SME growth and productivity…

39. Business Population Dynamics – A Primer
• Three things we need to remember as we seek to
understand the drivers of small firm growth:
– Churn
– Age
– Size
Anyadike-Danes, M and Hart, M (2017) “Firm and job dynamics in the United
Kingdom before, during and after the global financial crisis: Getting in under the
hood” chapter in OECD Business Dynamics & Productivity, April 2017
Anyadike-Danes, M and Hart, M (2016) “Peeling back the layers: separating the
effects of age and size on UK job growth, 2008–2015, ERC WP

40. Churn
• UK business population is in a constant state of flux.
• Each year around 250,000 firms are born and just over
200,000 die.
• So the population (currently just over 1.8 million) typically
grows a little, but underlying that growth are much larger
inflows and outflows of firms.
Source: Bespoke analysis from ERC UK Business Demography Database (1997-2017) – based on the
ONS Business Structure Database (BSD) – compiled from annual abstracts from the IDBR.

41. Age
• The most important factor conditioning firm performance is
age.
• Of the quarter of a million firms born in a particular year,
more than 80% are dead by age 10.
• Not only does survival depend critically on age, but growth in
jobs does too.
• By age 10 a relatively small proportion of the surviving firms
have grown, most that have grown have not grown very
much, and most of those that do grow at all do so in their first
five years.
Source: Bespoke analysis from ERC UK Business Demography Database (1997-2017) – based on the
ONS Business Structure Database (BSD) – compiled from annual abstracts from the IDBR.

42. Size
• Of the quarter of a million firms born in a particular year
around 90% have less than five employees.
• ….and around 85% of 10 year survivors still have less than 5
employees.
• However, size does have some effect: very small firms do grow
a little faster than larger firms, but have slightly worse
chances of surviving.
Source: Bespoke analysis from ERC UK Business Demography Database (1997-2017) – based on the
ONS Business Structure Database (BSD) – compiled from annual abstracts from the IDBR.

43. Job Creation & Destruction
• Analyse how the business stock in the private sector in the UK has
changed between 1998 and 2017 – specific focus on the key
dynamics of job creation and destruction.
• These metrics help us to understand the level of turbulence in jobs
and to analyse the type of firms which most contribute to job
creation / destruction in the UK.
• Using employee data, we examined the average annual job creation
and destruction rates between 1998-2017, as well as entry and exit
rates, and disaggregated both these by sector, size, age and region.
Source: See Hart, M; Anyadike-Danes and Bonner, K (2011) “Job Creation and Destruction in the UK – 1998-
2010” BIS Report October 2011 – available at
https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/32244/11-1326-job-creation-
and-destruction-uk-1998-2010.pdf Headline analysis updated in November 2017.

44. Definitions
• Job creation can be broadly defined as the positive gross
change in employment, summed over all businesses that
expand or start up between two points in time.
• Likewise job destruction is the negative gross change in
employment summed over all businesses that contract or
close between two points in time.
Source: See Hart, M; Anyadike-Danes and Bonner, K (2011) “Job Creation and Destruction in the UK – 1998-
2010” BIS Report October 2011 – available at
https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/32244/11-1326-job-creation-
and-destruction-uk-1998-2010.pdf Headline analysis updated in November 2017.

45. Job Creation & Destruction Update - 2017
Source: ONS Business Structure Database

46. Job Flows – 1 in 5 jobs changing
‘locations’ in 12 months
Source: Brief commentary on method and interpretation in ERC Blog December 2017 – available at
https://www.enterpriseresearch.ac.uk/turbulent-times-business-usual-4-5-million-jobs-created-
destroyed-12-months/

47. HIGH-GROWTH FIRMS?

48. Background
• During the last decade High-Growth Firms (HGFs) – sometimes
referred to as ’Scale-Ups’ – have increasingly become an
established feature of the UK business policy landscape.
• Indeed, HGFs are mentioned in the government’s recently
published policy document ”Building our Industrial Strategy”, and
are now considered sufficiently important that the Minister for
Small Business has taken on the role of ”Scale-Up Champion”.
• Whilst we know something of the characteristics of these firms –
about their age, size, sector and location – we know relatively little
about the dynamics of the HGF population as it evolves over time.
• For the most part attention is focused simply on the annual count
which is not an entirely appropriate measure of HGF activity.

49. Key Findings
• The average age at which a firm becomes categorised as a
High-Growth Firm (HGF) – that is, records its first High-Growth
Episode (HGE) – is about six years (see chart on next slide)
• Tracking HGFs over their lifetime, we show that almost two-
thirds of HGEs recorded during a 3-year period, and
conventionally referred to as HGFs, are actually repeat
episodes being recorded by HGFs ’born or first classified
some years previously (see chart on next slide).
• Although there is some variation across cohorts the picture
looks pretty consistent: by age 10, 40% of all 10+ firms have
experienced at least one HGE.

50. High Growth Episodes – Age
of Firm and Repeats?
• On average around two-
thirds of the HGEs recorded
by the UK’s HGFs are repeat
episodes.
• The widest swings occur in
and around the GR period,
with the largest shares
being recorded in 2008/11
and 2011/14.
• Looking at the average age
of HGFs – or rather the
average age at which a firm
records its first HGE.
• The most striking feature of
the age series is its
remarkable constancy – it
hardly varies at all –
average age is never
greater than 7 years, and
rarely lower than 6 years.

51. Start-up Cohort 1998 & HGEs

52. Summary of analysis of Cohort
1998:
Anyadike-Danes & Hart (2015)
“Fecundity, Fertility, Survival &
Growth: HGFs in the UK and their
contribution to job creation – a
demographic perspective” ERC
Working Paper (September 2015)
DOI: 10.13140/RG.2.1.3360.8089

53. Final Thought
• Having started the ball rolling a decade ago with our work for
NESTA (Vital 6%) we are now clearly of the view that “There’s
no such thing as a High-Growth Firm only firms that have
high-growth episodes”
• That should be the focus on policy moving forward and we
await the development of the business support offers in 2018!

54. PRODUCTIVITY

55. A Simple Story of Productivity! – 2008-15
Turnover
Growth
Job
Growth
Zero
Zero
‘Green
Zone’
+
+
+
-
-
-
Only one ‘space’
where growth in T/O;
Jobs and productivity
are all +ve – the ‘green
zone’
But sparsely
populated with firms –
approx. 10%
…and more than half
of them where there
is very little growth –
the blue triangle
Rule of thumb – 74%
of firms which grow
turnover grow
productivity; 21% of
firms which grow jobs
grow productivity

56. Productivity and OECD High-Growth
Firms?
• Only 20% of 10+ employee firms in the ‘green zone’ are HGFs (T/O
definition)
• Only 5% of 10+ employee firms in the ‘green zone’ are HGFs (Jobs
definition)
• So from a productivity perspective HGFs are not an important group of
firms

57. ‘Average’ productivity: a cautionary
tale
• The discussion has traditionally focused on ratios of outputs to inputs
computed at the economy-wide level, an average productivity measure
which we refer to here as the ‘aggregate’ measure
• Researchers now have access to firm-level performance data and can
compute an average productivity measure directly from firm-level
productivity levels which we refer to here as the ‘mean’ measure

58. 58
Mean Vs Aggregate Productivity – summary statistics
2008 2015 2015/08
units ratio
firms number 250323
turnover £bn 1393.85 1929.82 1.385
jobs 000 9656.1 10137.4 1.05
turnover per firm £m 5.57 7.71 1.384
jobs per firm number 38.57 40.5 1.05
average turnover per
job: 'aggregate' £'000 144.35 190.37 1.319
average turnover per
job: 'mean' £'000 160.2 170.8 1.066

59. 0
0.05
0.1
0.15
0.2
0.25
0.3
1
1.6
2.7
4.5
7.4
12.2
20.1
33.1
54.6
90
148.4
244.7
403.4
665.1
1096.6
1808
2981
4914.8
8103.1
13359.7
22026.5
36315.5
ratio
turnover per job (tperj) £K
Figure 2: productivity by firm size, selected sizes,
relative frequency ratio, 2008 (log scale)
1.6 jobs 2.7 jobs 90 jobs 148.4 jobs

60. What have we learned?
• Measurement matters: different measures of “average productivity” and
its growth are not created equal
• Size matters too! The relationship between productivity and firm size is
quite subtle: a large proportion of all sizes are concentrated in the middle
of the productivity distribution. There are slightly more smaller firms
below the middle, and slightly more larger firms above the middle
• There are “long tails” of both under-performing and over-performing firms
particularly at the small end of the firm size distribution

61. And turning to innovation and
innovation support …

62. Innovation and productivity
(adapted from the OECD)
Growth at the global frontier
Growth at the national frontier
Growth of non-frontier firms
Diffusion of NTF innovation
Diffusion of NTF innovation
NTM
innovation
Aggregate
Productivity
Growth

63. The geography of NTM and NTF
innovation in England

64. Does partnering matter for NTM and
NTF innovation?
• Does partnering matter for
NTM and NTF innovation?
• Micro-firms in NI (N=1000)
– the extreme case of
limited absorptive
capacity?
• OTOH very small firms may
have the most to gain
from partnering
• Key result: Partnering
matters in both cases but
NTM networks can be
broader
Source: Roper, S., & Hewitt-Dundas, N. (2017). Investigating a
neglected part of Schumpeter’s creative army: what drives new-to-
the-market innovation in micro-enterprises? Small Business
Economics, 49(3), 559-577.

65. Can working with a university influence
NTM innovation and its success?
• Collaborating with universities will reflect the
type of knowledge the firm is seeking as well
as their own internal knowledge profile
• Provide frontier-edge knowledge for NTM
innovation
• Reduced risk of moral hazard
• Offset by two-worlds paradox (Hall, 2003;
Bruneel et al. 2010) differences in
institutional logics and priorities may lead to
tensions around project timelines, rewards,
commercialisation and administrative
procedures
• Can learning from prior collaboration help
firms to overcome this paradox?
• Analysis of the UK Innovation Survey with
different finding for larger and smaller firms
Prob of
NTM innov
Sales of NTM
innov
Small +22 % +1.3%
Medium +21 % +15.8%
Large + 21 % +12.3%
Source: Nola Hewitt-Dundas, Stephen Roper & Areti Gkypali (2016) Can learning help
to overcome the ‘two-worlds’ paradox in university-business collaboration?
Effects of university collaboration by
firm size
Key findings
1. University collaboration is good for
NTM innovation but….
2. There is an issue in the
commercialisation of NTM
innovation in smaller firms

66. Adopting TQM or ISO 9000: The
implications for innovation?
• What happens to innovation when a firm
adopts a new quality improvement method?
• Does this effect differ between ’hard’ (rule
based) QIMs and ‘soft’ (organisational)
QIMs?
• Considered this for sample of Irish
manufacturing firms (n=1358)
• Evidence of larger disruption effects from
(hard) ISO 9000 than (soft) Quality Circles.
TQM is somewhere in between. Long term
effects are beneficial.
• Lesson: Quality improvement and innovation
should be considered together. Anticipate a
short-term hit too.
Time
Innovation
Output
A B
I1
I2
I3
Source: Bourke, J and Roper, S (2017)
Innovation, quality management and learning:
short-term and longer-term effects, Research
Policy, forthcoming but available on-line.

67. Assessing the effectiveness of UK
innovation support
• UK policy delivered through InnovateUK and the
other research councils (particularly EPSRC)
focuses on supporting NTM innovation
• Our analysis matches projects (GTR) with data
on business performance (BSD) over 2006-16
period
• This covers grants provided to over 10,000 firms
and we compare the performance of these firms
to a closely matched control group
• Firms participating in UK Research Council
projects (including Innovate UK) grew their
turnover and employment 22.5-28.0 per cent
faster in the six years after the grant, than
similar firms which did not receive support.
• The net effect is a 6.2 per cent productivity
boost after 6 years.
Source: Vanino, E Roper, S and Becker, B (2017) ‘Assessing the business performance effects of engagement with publicly funded
science’, ERC Research Paper 61
0 20 40 60
All firms
Manuf - HT
Manuf - LT
Services - KI
Services - NKI
Micro
Small
Medium
Large
Top Quartile
2nd Quartile
3rd Quartile
4th Quartile
Turnover growth effects

68. Additionality by productivity quartile
0
20
40
4th 3rd 2nd 1st
0
50
100
4th 3rd 2nd 1st
-20
0
20
40
4th 3rd 2nd 1st
Employment growth effects
Turnover growth effects
Productivity growth effects

69. Additionality by productivity quartile
0
20
40
4th 3rd 2nd 1st
0
50
100
4th 3rd 2nd 1st
-20
0
20
40
4th 3rd 2nd 1st
Employment growth effects
Turnover growth effects
Productivity growth effects
60.35
11.555.722.5
0
100
1st2nd3rd4th
Allocation of support for business R&D

70. The key lessons …
For policy
• L1: Marked differences exist between
innovation performance in different
parts of the UK. We need to understand
this better.
• L2: We have some effective instruments
for NTM innovation but we need to
refine our targeting to maximise
productivity impacts
• L3: Connectivity generally and
University-Business collaboration are
good for innovation. We may need to
do more to broker and help
commercialise outcomes for smaller
firms .
For managers
• L1: Partnering matters for
innovation, particularly for
smaller, independent companies.
• L2: Working with universities and
in research grants has positive
innovation and growth benefits
• L3: Innovation may be strongly
influenced by other managerial
actions such as quality
improvement. Be careful to keep
your eye on the ball !

71. @ERC_UK
ERC State of the Art
(SOTA) Reviews

72. Overview
• A publication innovation for the ERC
• Short (3-4 pages) reviews of the state of
evidence/knowledge on specific, topical
issues/questions
• Clearly summarise a range of sources of relevant and
robust research and policy literature – noting key
evidence points and resources for further information
• Commissioned from UK and international experts
• Provide an opportunity to widen ERC expert networks
and contacts
• Propose to produce 20 SOTA reviews in Year 1, and 10
in both subsequent years

73. Questions
• What would be your suggestions for priority
themes/questions for the SOTA reviews?
• Examples…
– What policies are most effective in encouraging
greater female entrepreneurship?
– What does the evidence tell us about the relationship
between ambition and innovation in SMEs?
– What is the relationship between exporting and
productivity in SMEs?
…Over to you!

74. Mark Hart and
Stephen Roper
Planned ERC Activity
2018-20

75. Key ERC activities
• Knowledge creation
– Core research programme agreed with ERC Funders Group – for 2018-
21 this has an increasing emphasis innovation and productivity
– Commissioned projects - more specific (and sometimes short-term)
one off projects for Funders and other organisations
• Knowledge integration and synthesis
– SOTA reviews
– Data development and matching
– Advisory roles and responsive activities (e.g. HMRC)
– Consultancy (e.g. OECD, HS2)
• Engagement, influence, impact
• Capability building – internal and external

76. Core research projects 2018-19
Feb-May Themes June to January 2019 February 2019-September 2019
State of
the Art
(SOTA)
Briefings
on key
aspects of
SME
growth
and
developm
ent
Finance and
Investment
Investing for the future? Investigating
the determinants and barriers of
investment in smaller firms
Investment, non-borrowing and place. How
does SMEs’ willingness to invest and borrow
vary with place? How has this changed
through time?
Leadership
and
management
practices
Leadership and management practices
and the take-up of innovation. How do
internal and boundary spanning
management practices influence
adoption in different sectors and
localities?
L&M capabilities – levering external assets
for growth –How do internal and boundary-
spanning management practices enable firms
to most effectively take advantage of such
external resources?
Innovation
and growth
Innovation and productivity in SMEs –
which types of innovation and which
combinations of innovation drive SME
productivity?
Knowledge to money – What are the links
between IP protection, innovation and
growth?
Diffusion and
productivity
Understanding local productivity
disparities – What explains
productivity differences between local
areas?
Learning from the best (i.e. most productive)
SMEs – What are the most productive SMEs
doing right? How can we effectively diffuse
these practices?

77. Commissioned projects
Business resilience in disadvantaged groups (£750k,
JP Morgan Foundation, 24 months, Nov 2017)
• Analysis of personal and business resilience
among business founders from disadvantaged
communities
• ERC leading 5 country study with research
partners in Spain, Italy, France and Germany
• Key outputs: Research outputs and business
development tool kits
Micro-business Britain (c. £500k, BEIS, Nov-March
2018)
• Survey of c. 11,000 micro-businesses in UK,
Ireland and the US with a focus on tech diffusion,
innovation and ambition
• Partners in the US (Georgia Tech) and Ireland
(Cork) (Pro-bono)
• Key outputs: Research dataset covering key IS
strategy issues
Diffusion and Productivity in Foundries and Metal
Forming Companies (£400k, IS Funding, 36 months )
• Which innovations have driven productivity
growth? How can we encourage their wider
diffusion?
• ERC working with two industry associations for
the two sectors
• Key outputs: Research outputs and practice
models for developing diffusion
Other projects:
Design economy 2017 – Design Council, £60k, Jan to
April 2018
Impact assessment of Account Management –
Scottish Government, £23k, Nov to April 2018
SMEs in NI – set of projects for Department for the
Economy (NI), £75k, March 2018-19
Growth Hub data matching and analysis- BEIS

78. Data development and integration
• Key aspect of ERC work has been addressing UK data deficit – UK
and in partnership with OECD (Dynemp; Multiprod)
• Key data sources and matching:
– Business Structure Data UK Innovation Survey
– Employer Skills Survey Longitudinal SB Survey
– SME Finance Monitor Insolvency service data
– Gateway to Research CRM data
• Main new addition in 2018 will be IPO data and hoping to build IP
histories for firms to set alongside performance and innovation data
• ERC also support the User Groups for the Longitudinal Small
Business Survey and the UK Innovation Survey

79. Vicki Belt
ERC Impact and
Engagement Plans
2018-2021

80. ERC Strategic Goals
To be THE UK’s ‘go to’ centre of research expertise on SME
growth, innovation and productivity
• Providers of independent, trusted data and insight, based
on rigorous analysis
• Delivering relevant research that focuses on the issues
that policy makers and businesses face
• Giving useful advice, and practical, actionable
recommendations

81. Context
• UK is facing big challenges - Brexit; Industry 4.0; productivity gap
• Rapid pace of change for policy makers and businesses
• Increased demand for timely insights and advice from trusted
sources. But…
“Major hurdles remain in connecting policy makers with the wider
research community”.
Policy makers are looking for: ‘honest brokers’, ‘expert advice’
‘impartiality’, ‘a guide to current thinking’.
(Lawrence, et al, 2016)
• Clear need for information that is accessible, properly packaged and
communicated

82. Firm foundations
• ERC has many key strengths:
– Good networks – policy, academic and business
– Responsiveness and flexibility
– Openness and willingness to share expertise
– Range of research outputs
– Highly regarded stakeholder-focused events
– Solid infrastructure

83. Phase 3: Building on success
Maximising impact
• More structured
stakeholder contact
management
• More defined project
focus (…with flexibility
built in)
• Focus on producing
accessible outputs
• More research synthesis
Widening awareness
• Nation-wide
engagement
• Increased media activity
• Increased social media
presence

84. Mechanisms/activities
Stakeholder engagement
• Initial stakeholder mapping, and development of a new strategy
• New steering committee, and refreshed advisory panel
• Project advisory groups, milestones and communications plans
• Annual conference, seminars and workshops
Outputs
• Policy briefings, infographics and blogs
• SOTA Reviews
• Annual State of Small Business Britain report
Dissemination
• Ring-fenced budget for media/PR activity, use of Comms Agency and wider
connections
Evaluation
• New KPIs
• Ongoing monitoring and feedback

85. Engaged scholarship
Research
idea
Research
design
Ongoing
research
Analysis
Outputs and
dissemination
Post-research
phase
Engage
Stakeholder
identification,
mapping and
approach
Mutually
define aims,
engagement
plans, impact
pathways
Communicate
and review
progress, address
issues
Share emerging
findings, discuss and
mutually interpret
meaning
Discuss and agree
how to best
present findings,
integrate
stakeholders in
dissemination
activity
Maintain
stakeholder
relationships,
review and
monitor impact
capture learning
Impact

86. @ERC_UK
Feedback on themes
for ERC State of the
Art (SOTA) Reviews

87. Thank you!
Questions and comments?
More information at http://enterpriseresearch.ac.uk/
Contact us:
Steve Roper stephen.roper@wbs.ac.uk
Mark Hart mark.hart@aston.ac.uk
Vicki Belt vicki.belt@wbs.ac.uk
This work contains statistical data from ONS which is Crown Copyright. The use of these data does not imply the
endorsement of the data owner or the UK Data Service at the UK Data Archive in relation to the interpretation or analysis of
the data. This work uses research datasets which may not exactly reproduce National Statistics aggregates.