Presentation by Maksim Belitski, Associate Professor in Entrepreneurship and Innovation, Reading University, UK at the seventh meeting of the Spatial productivity Lab of the OECD Trento Centre held on 20 February 2020.

1. www.henley. ac.uk20 February 2020
Maksim Belitski, University of Reading, Tatiana Stettler, Kent State
University , William Wales, University of Albany , Jeff Martin,
University of Alabama
Spatial productivity for regional and local development – 7th
meeting , February 20th , Trento, Italy
Speeding up and scaling up firm growth:
An investigation of the organisational, industry
and regional drivers

2. • Firm growth is a complex phenomenon (see McKelvie and
Wiklund, 2010 for an overview).
• Recently, attention has been directed at the speed with which
firm’s achieve growth (Hoffman and Yeh, 2018). On the
extreme end of the spectrum, Google (Alphabet), Facebook,
and Amazon exemplify firms that were able to grow
remarkably fast.
• Venture capitalists focus on these disruptive technology firms
and fund them furiously, advancing their speed of growth. The
idea is to scale fast and seek huge returns for investors.
2
Why studying firm growth ?

3. Growing fast is not for all: only a small number of firms are able
to grow and accelerate it over time.
At the extreme, high-levels of acceleration are characteristic
and definitive of blitzscaling, even to the extent that some
companies prioritize growth speed over efficiency (Hoffman
and Yeh, 2018; Kuratko et al., 2020).
Both start-ups and mature firms can grow fast, providing huge
returns for investors.
Researchers, practitioners and policymakers continue to
question what factors propel firm’s (startups and incumbents)
chances to grow rapidly and become a more powerful
economic driver.
3
Blitzscalers and firm’s growth

4. • This study investigates factors that allow firms not only to
maintain their speed or rate of growth (Jansen and Roelofsen,
2018; Hoffman and Yeh, 2018; Josefy et al., 2015), but also
accelerate it over time.
• This occurrence, the acceleration of firm growth speed, is the
central phenomenon of our study.
• We do so without concern for the rate at which scale is
achieved. This enables us to study firm growth acceleration
among a much wider sample of firms than would be possible
when focusing on blitzscaling or unicorns, which represent
outliers in the overall population of business firms (Hoffman
and Yeh, 2018).
4
Aim

5. • Firm acceleration is defined in this study as the ability of an
organization to sustain a rate of growth in which
subsequent periods exceed preceding levels of growth.
• Thus, we refer to firm acceleration as “changing the speed of
growth” (Foley, 2012).
• Originally, the concept of acceleration emanates from
physics (e.g., Bondi, 1964), where it is viewed as a measure
of the rate of change of velocity resulting from a
combination of various forces on a physical object.
5
Definition

6. • Once a firm has defined its product, it begins to penetrate the
market and hire employees to expand its market reach. Market
commercialization requires a boost in labor.
• Adding employees to the existing firm enriches the quality of its
products and services through synergies and creates a critical
mass of skills and capabilities to accelerate (Jansen, 2004).
• Larger firms have more resources to draw upon to recognize
and exploit new opportunities (Eisenhardt and Martin, 2000;
Matusik and Heeley, 2005)
• Hypothesis 1a: Firm size accelerates firm growth
6
Theoretical framework

7. Prior research suggests that firm age is also an important
determinant of firm growth (Haltiwanger et al., 2013; Lawless,
2014).
Yet unlike firm size, it is negatively associated with growth (Evans,
1987; Dunne and Hughes, 1994; Yasuda, 2005; Calvo, 2006;
Haltiwanger et al., 2013). Daunfeldt et al. (2014) and Coad et al.
(2018) found that high growth firms are on average younger than
other firms.
Over time, firms’ strategic focus shifts from opportunity-seeking
(exploration) to advantage-seeking and niche (exploitation).
• Hypothesis 1b: Firm age de-accelerates firm growth.
7
Theoretical framework

8. • Firm growth may depend on incumbents who have
accumulated resources and prevent other firms from accessing
those, by creating resource deficits (Bradley et al. 2011)
• Barriers to resources lead to fewer opportunities for scaling as a
result of gaining market competitive advantage. In the context
with limited resources and barriers makes commercialization
complex.
• Firms solve market problems quicker if the industry ecosystem
is more competitive.
• Hypothesis 2a: Industry competition accelerates firm growth
8
Theoretical framework

9. • As the completive context changes, a firm may decide to
change (switch) industries. Firms switch industries for a variety
of reasons.
• Novel competitive landscapes require adaptation of existing
routines and practices, time to reach a new portfolio of
suppliers and customers, and such changes call for different
types and combinations of firm capabilities (Nonaka, 1994;
Zahra et al. 2006). This may inhibit firm’s growth.
• “Do not change horses in midstream” from an 1864 speech by
Abraham Lincoln in reply to Delegates from the National Union
League.
• Hypothesis 2b: Switching industry de-accelerates firm growth
9
Theoretical framework

10. • Firm’s location in a region with a high share of knowledge
intense business sectors (KIBS) enables easier access to
knowledge spillovers and knowledge collaborations (Acs et al.,
2009; Roper et al. 2017).
• Due to the considerable strategic interdependence of firms in
KIBS and the complexity of product development, co-location
with KIS firms enables other firms and entrepreneurs to access
tacit knowledge and commercialize it (Audretsch and
Feldman, 2004).
• Hypothesis 3a: Firm’s location in a region with a higher share of
knowledge-intense sectors accelerates firm growth
10
Theoretical framework

11. • Knowledge spillovers are not limited to a region but also
emanate from multinational enterprises located in a region
(Driffield et al., 2014).
• Pecuniary or ‘pure’ knowledge spillovers arising from a co-
location and interaction between MNEs and local firms
(Boschma, 2005; Driffield et al., 2014) could add to firm
resources and absorptive capacity, increasing the likelihood of
new product creation and imitation, both accelerating firm’s
sales and employment locally and internationally.
• Hypothesis 3b: Regional knowledge spillover emanating from
foreign firms accelerates firm growth
11
Theoretical framework

12. 12
Conceptual model

13. • We test our hypotheses using the Business Registry, BSD data
during the period of 2000-2017. The BSD snapshot contains
limited information (turnover, employment, industrial
classification for example), but offers researchers a full sample
of active firms in the UK to work with.
• Sample = 20,857,072 observation available out of originally
available 33,807,849 observations, after cleaning for the
missing values of the variables of interest, as well as non-active
and dormant firms. When controlling for several regional
characteristics in a region (Tables 3-6, specification 4) our
samples drops to 9,220,892 observations.
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Data

14. 14
Year split
Sample BSD original Reduced
Sector # obs. Share Sector # obs.
2000
2001
2002
2003 1093976 5.25
2004 1097725 5.26
2005 1110521 5.32 971504 10.54
2006 1311818 6.29 902937 9.79
2007 1367484 6.56 801050 8.69
2008 1416552 6.79 857998 9.30
2009 1430144 6.86 887602 9.63
2010 1406859 6.75 882935 9.58
2011 1474972 7.07 805963 8.74
2012 1480744 7.10 736991 7.99
2013 1467340 7.04 643626 6.98
2014 1472764 7.06 618764 6.71
2015 1525232 7.31 576763 6.25
2016 1563226 7.49 534759 5.80
2017 1637715 7.85
Total 20857072 100 9,220,892 100

15. Sample BSD original Reduced
Sector # obs. Share # obs. Share
Manufacturing 1505627 7.22 659082 7.15
Utilities 77650 0.37 35227 0.38
Construction 2640658 12.66 1086685 11.79
Wholesale and retail 3795145 18.20 1675318 18.17
Transportation and storage 1059331 5.08 486030 5.27
Accommodation 1270436 6.09 523019 5.67
Information and communication 1416990 6.79 605869 6.57
Financial and real estate 1075842 5.16 480367 5.21
Profession. and scientific services 3450201 16.54 1555968 16.87
Public admin and education 1908786 9.15 675847 7.33
Health and social activities 897350 4.30 567939 6.16
Arts and entertainment 741529 3.56 376051 4.08
Other consumer services 1017343 4.88 493490 5.35
Total 20857072 100.00 9,220,892 100.00
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Industry split

16. Sample BSD original Reduced
Region # obs. Share Firm size in FTEs # obs.
North East 551123 2.64 303469 3.29
North West 2065878 9.90 585954 6.35
Yorkshire and
The Humber
1490576 7.15 719496 7.80
East Midlands 1429961 6.86 621230 6.74
West Midlands 1707136 8.18 680065 7.38
East England 2146545 10.29 1031354 11.18
London 3347193 10.05 2075477 22.51
South East 3401090 16.31 1980563 21.48
South West 1921229 9.21 637737 6.92
Wales 835543 4.01 395517 4.29
Scotland 1387796 6.65 189900 2.06
Northern Ireland 573002 2.75 130 0.001
Total 20857072 100 9,220,892 100
16
Region split

17. Sample BSD original Reduced
Firm size in FTEs # obs. Share Sector # obs.
Micro 1-9 17644788 84.60 7721623 83.74
Small 10-49 2609149 12.51 1203487 13.05
Medium small 50-99 305173 1.46 147550 1.60
Medium large 100-249 172668 0.83 83784 0.91
Large >249 125294 0.60 64448 0.70
Total 20857072 100 9,220,892 100.00
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Firm size split

18. 18
Descriptive stats

19. 19
Logistic regs: Firm acceleration in sales

20. 20
Logistic regs: Firm acceleration in market size

21. 21
Logistic regs: Firm acceleration in employment

22. 22
Logistic regs: Firm acceleration in labour
productivity

23. 23
Discussion
• Recent studies have suggested that only a small fraction of
firms experience rapid growth (Davidsson et al. 2013; Josefy et
al., 2015; Coad et al., 2016, 2018), and those who create most
of new jobs (Daunfeldt et al., 2015) , invest in technology,
improve productivity, generate knowledge spillovers.
• Previous studies have predominantly focused on scale-ups
and high growth firms and relied on static analysis. Policy
implications from these studies are limited as it is difficult to
explain the causality of the phenomenon if firm acceleration
in fact is random, i.e., if firms who accelerate in one period, in
general, do not accelerate in the previous periods.

24. 24
Discussion
• This study demonstrates that firm acceleration in a specific
point in time depends on the persistence of acceleration and
on the multi-level forces.
• Firm acceleration is often the result of a firm transition from
market experimentation to market exploitation. Firm age and
firm size in this regard remain important predictors of firm
acceleration (Haltiwanger et al., 2013).
• There is a lack of understanding how multi-level forces work
in tandem to exert upon a firm to enable acceleration.
• Replicating the study of these factors in different countries
beyond the UK is possible.
•

25. 25
Thanks for listening