Journal of Small Business and Enterprise Development
Small business performance: business, strategy and owner‐manager characteristics
Robert A. Blackburn Mark Hart Thomas Wainwright
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20,1
Small business performance:
business, strategy and
owner-manager characteristics
8
Robert A. Blackburn
Small Business Research Centre, Faculty of Business and Law,
Kingston University, Kingston-upon-Thames, UK
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Mark Hart
Economics and Strategy Group, Aston Business School, Birmingham, UK, and
Thomas Wainwright
Management School, University of Southampton, Southampton, UK
Abstract
Purpose – This paper aims to contribute to the understanding of the factors that influence small to
medium-sized enterprise (SME) performance and particularly, growth.
Design/methodology/approach – This paper utilises an original data set of 360 SMEs employing
5-249 people to run logit regression models of employment growth, turnover growth and profitability.
The models include characteristics of the businesses, the owner-managers and their strategies.
Findings – The results suggest that size and age of enterprise dominate performance and are more
important than strategy and the entrepreneurial characteristics of the owner. Having a business plan
was also found to be important.
Research limitations/implications – The results contribute to the development of theoretical and
knowledge bases, as well as offering results that will be of interest to research and policy communities.
The results are limited to a single survey, using cross-sectional data.
Practical implications – The findings have a bearing on business growth strategy for policy
makers. The results suggest that policy measures that promote the take-up of business plans and are
targeted at younger, larger-sized businesses may have the greatest impact in terms of helping to
facilitate business growth.
Originality/value – A novel feature of the models is the incorporation of entrepreneurial traits and
whether there were any collaborative joint venture arrangements.
Keywords Small business performance, Entrepreneurial traits, SME growth, United Kingdom,
Entrepreneurialism, Small to medium-sized enterprises
Paper type Research paper
Journal of Small Business and
Enterprise Development
Vol. 20 No. 1, 2013
pp. 8-27
q Emerald Group Publishing Limited
1462-6004
DOI 10.1108/14626001311298394
Introduction
The prominence given to the role of small and medium-sized enterprises (SMEs) in the
UK economy has been renewed following a period of decline in the 1950s and 1960s
(Stanworth and Purdy, 2003). SMEs account for 99.9 per cent of all enterprises in the
UK economy (Department for Business, Innovation and Skills, 2011), a figure that is
reflected worldwide. However, it is universally recognised that the small business
population is not a homogenous group (Forsman, 2008). Businesses are started for
many different reasons, are run by owners with various aspirations and abilities, have
vastly different internal organisational characteristics, and are located in a range of
sectors and locations (Wijewardena et al., 2008). Recently there has been a call for more
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research on the relationship between the manager and growth in small firms
(e.g. Andersson and Tell, 2009;), an issue that this paper revisits. Subsequently, the
objective of this paper is to contribute to debates concerning business growth. Hence,
this paper builds on a growing body of literature that attempts to develop and test
conceptual frameworks for an understanding of the determinants of small firm growth,
which could help governments to assist small firms in achieving faster rates of growth
(see, for example, Barkham et al., 1996; Hart and Gudgin, 1999; Hart and Roper, 2004;
Dobbs and Hamilton, 2007; Kirkwood, 2009; Littunen and Niittykangas, 2010). It is
important here to note that there are problems of establishing causality with
quantitative studies and that the relationships are not simply linear, and nor are the
factors that affect growth easily captured and modelled (Storey, 2011).
Nevertheless, researchers tend to agree on the need to consider both organisational
and owner manager characteristics in understanding business growth. For example,
the multivariate model of SME growth, developed from an UK inter-regional study
(Barkham et al., 1996), identified six characteristics of managers and 11 aspects of
managerial strategy, which, along with variables controlling for size, sector and region,
accounted for half of the difference in turnover growth between small firms.
Ultimately, this paper seeks to assess the relative contribution of firm, strategy and
owner-manager characteristics to business performance. The novelty of the analysis is
within the area of owner-manager characteristics, which are developed to include a
typology of entrepreneurial types, generated from the self-definitions of respondents.
These variables are then utilised within a series of logit models of SME growth, which
control for firm, strategy and owner-manager characteristics to offer some indication of
relative importance of these different factors on business performance.
Understanding business performance – new debates
Contemporary studies in small business and entrepreneurship have often placed firm
growth at the centre of their inquiry, whilst writers such as Sexton and Smilor (1997)
have gone as far as to place growth at the heart of entrepreneurship theory (Steffens
et al., 2009). Similarly, the business media and policy-makers have also remained
fixated by the issue of small firm growth (Nicholls-Nixon, 2005; Storey, 2011).
Although debates on growth and performance are well embedded within the
traditions of small business and entrepreneurial scholarship (e.g. Penrose, 1959),
recent debates have begun to turn to present a more critical stance on earlier work
(Barringer et al., 2005; Coad, 2009; Storey, 2011). For example, Blackburn et al. (2009)
have argued that whilst research on firm growth is an established area, the field
suffers from a limited empirical evidence base, whilst Leitch et al. (2010) view the
study field as being theoretically weak. One such criticism has focussed upon stage
models of growth that are not based on evidence, but are reliant on normative
assumptions (Gibb, 2000).
A recent review by Levie and Lichtenstein (2010) explored 104 growth models
identified within the literature and found no similarities between activities that
occurred at particular stages of growth, highlighting the need for more empirically
robust studies. More recent research has sought to provide detailed and nuanced
understandings of growth. A detailed study by St-Jean et al. (2008) highlighted how
firm growth is nonlinear and temporal, and subject to a series of complex factors that
determine growth, both within and outside of the firm, problematising models of
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10
continuous growth. In other words, few firms experience sustained growth throughout
their lifecycle (Mazzarol et al., 2009; Storey, 2011). In comparison, Davidsson et al.
(2009) have challenged the uncritical promotion and adoption of growth strategies by
firms that are not initially profitable, and only experience short-term growth,
highlighting how the promotion of growth to firms should perhaps be more
strategically targeted. Subsequently, this paper will seek to offer contributions that
address the theoretical and empirical weaknesses of studies on growth.
Earlier work by Storey (1994) provided a framework that attributes the emergence
of growth from the intersection of three spheres:
(1) the entrepreneur;
(2) strategy; and
(3) the firm.
Hansen and Hamilton (2011) note that whilst these elements are important, the
difficulty in identifying which firms grow is uncovering the specific configurations of
these three elements. Storey’s (1994) framework, and the three elements within it, are
present in many variable centred studies (Dobbs and Hamilton, 2007). This paper seeks
to follow this framework and explores a range of personal, organisational and strategic
factors and their relationships with business performance, before discussing the
results of the analysis within a multivariate framework.
We utilise three main measures of business growth and performance, including:
.
employment change over the previous two years (2000-2002);
.
turnover change for the previous three years (in real terms, 1999-2002); and
.
profitability (whether or not the business had made profits over each of the
previous two years).
Drawing upon Storey’s (1994) conceptual framework outlined earlier, the paper groups
the factors for investigation into three linked areas:
(1) business characteristics;
(2) owner-manager characteristics; and
(3) business strategy.
With regard to business characteristics, studies have suggested that major differences
in the performance of firms can occur from sector and location (Storey, 1994), whilst
research on the size and age of enterprises has indicated that older and larger firms are
more likely to have lower growth rates (Davidsson et al., 2006; Hamilton, 2012). Much
of the economics literature on the determinants of small firm growth has focused on the
combination of life cycle effects (Reid, 1993; Beck et al., 2005; Chiao et al., 2006). These
have often used resource-based theory to consider the role of firm assets, for example
Rangone (1999) and Davidsson et al. (2006), where the early acquisition by firms of
resources that are difficult to replicate by competitors provides them with the ability to
develop a competitive advantage, facilitating growth. The growth literature also
suggests that newer, smaller firms, are more flexible, and are able to discover new
opportunities that enable them to undertake bursts of growth, where larger firms are
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slower to react, as the decision-making powers of managers is often further away from
the market (Escribá-Esteve et al., 2008; Steffens et al., 2009).
Moving away from the analytical unit of the SME, performance has also been linked
to the growth aspirations and motivations of owner-managers (Wiklund and Shepherd,
2003), as well as their psychological characteristics and “antecedent attributes” (Burns,
2001), including education and prior experience (Richbell et al., 2006; Delmar and
Wiklund, 2008) and capabilities (Barbero et al., 2011). It is frequently argued that
owner-managers are the most important resource within a firm, and their commitment
to growth is instrumental in shaping performance and growth (Smallbone et al., 1995;
Mazzarol et al., 2009; Hansen and Hamilton, 2011). Whilst quantitative studies have
struggled to capture adequately the multidimensional nature of growth, qualitative
studies have begun to emphasise the influence of owner characteristics on business
goals, processes and performance (e.g. Barringer and Jones, 2004).
Conventional factors within this area often include the age of business owners,
educational levels and gender (for a review, see Westhead and Wright, 2000; Dobbs
and Hamilton, 2007). Elsewhere, Sadler-Smith et al. (2003) suggested that
entrepreneurial style, not management behaviour, is positively associated with the
probability that a firm would be a high-growth type. Our study seeks to build upon this
area of research by deploying a methodological “innovation” and including
owner-managers’ self-definitions of business style, as defined in the Methods section.
The third element, business strategy, has received considerable attention, regarding
the importance of changing firm strategy to cope with the demands of the changing
external environment and by internally managing the firm during phases of growth
(St-Jean et al., 2008). Debates surrounding business strategy and growth have
questioned the role of planning in strategy formation, although these debates have
been inconclusive, with no decisive evidence to suggest that planning is important, or
not, in strategy formation (Fletcher and Harris, 2002). Planning and the development of
strategy vary between formal and informal plans, although firms that actively engage
in formal planning are in the minority (Richbell et al., 2006).
Formal planning approaches have been criticised for failing to represent reality, and
changing environments that are uncertain, especially where information is not
available to the owner-manager, where the development of a plan may not be effective
in improving firm performance (Fletcher and Harris, 2002). Subsequently, it has been
argued that strategies that emerge over time and are flexible and unconstrained, are
more useful to small firms, and that the practice of firm planning, is more important
than the development of a written document, for strategy formation (Lyles et al., 1993).
Despite these views, Richbell et al.’s (2006) study finds that firms with growth
strategies also had formalised plans, supporting the argument that firms need to
balance their resources and deploy them strategically in their activities, to obtain
growth (Kemp and Verhoeven, 2002; Mazzarol et al., 2009).
Overall, whilst the paper seeks to contribute to the accumulation of knowledge on
the factors that influence business performance based on a priori reasoning, it also
introduces new issues to the research agenda. Further, our study sought to gauge the
relative strength of the above three areas (i.e. firm characteristics, business owner traits
and choice of business strategy) on business performance. As such, this paper will
contribute to these critical debates on growth by providing empirically robust findings.
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Methodological considerations
Macro surveys of SMEs are now relatively plentiful and have been conducted for
decades (e.g. Bank of England, 2002; Small Business Service, 2003; Business Enterprise
and Regulatory Reform, 2009; Centre for Business Research, 2009; Department for
Business, Innovation and Skills, 2011). However, studying firm growth brings with it a
number of methodological challenges (Davidsson and Wiklund, 2000; Storey, 2011).
This paper draws on a telephone survey of 360 firms undertaken in 2002 that
selected businesses randomly within stratification criteria based on employment size,
age of business and sector. Target quotas were set for these parameters to enable
quantitative analyses. The sample was drawn from the following UK regions: South
West, South, South East and Greater London. The response rate for the survey was 33
per cent, including businesses who requested a “call back” but were excluded because
the target of 360 interviews was achieved. Interviews were held with the
owner-manager, managing director or CEO of the enterprise.
This survey focuses on firms employing between five and 249 people in specific
areas of business activity. For brevity, we will refer to these as SMEs, although it is
acknowledged that the term SME generally also includes businesses with 0-4
employees. Although this size cohort constitutes around 10 per cent of all enterprises in
the UK, it is argued that it captures a dynamic segment as it excludes part-time and
one-person firms and the minimum efficient size is more likely to have been met, whilst
more systematic methods of management and operations to have been implemented. It
is also arguable that these enterprises may play a more important role in economic
growth and are run by employers with aspirations of growth and who are prepared to
take on additional employees. Within this size cohort, there will also be vast differences
in performance. It is this variation in performance that we seek to explore.
The sample consists of manufacturing (17.8 per cent), retail, wholesale and
distribution (20.6 per cent), hotels and catering (17.8 per cent), professional services
(17.2 per cent), creative and marketing industries (12.2 per cent), and consumer services
(14.4 per cent), where the value in parentheses consists of the relative percentage of
firms by sector in the sample.
Whilst the paper provides much needed empirical evidence and analysis on growth,
it does have some limitations. First, the paper relies on a cross-sectional dataset of
SMEs, which limits the depth of the analysis. Second, given the discontinuous nature of
business growth, a snapshot survey may not be able to capture variations of
performance over long periods of time. Third, the performance variables were collected
from the same survey, which means that it suffers from common-methods bias.
However, this is typical of most SME research, because of the absence of secondary
performance data.
Business characteristics
Financially, the businesses showed a broad range of turnover: 9.4 per cent of the firms
had a turnover of less than £100,000 and a further 42.2 per cent had turnover of
between £100,000 and £500,000. An enterprise’s age frequently influences its
organisational, process and product characteristics. In this sample, less than one-third
of the SMEs were under five years old, and a third were more than 20 years old, and
had averages of 12 (median) and 24.4 (mean) years. The average employment size of
enterprises in the sample was 15.6 (mean) and ten (median) people. The employment
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distribution of males and females in the enterprises was approximately even – 47.8 per
cent were women and 52.2 per cent were men. The majority (66.5 per cent) of those
employed by the sample were full-time staff, although approximately one-third were
part-time.
Owner-manager characteristics
Age of owner-managers
Just over one-third of owner-managers were in their forties, and the sample
respondents overall had an average (mean) age of 46. This reflects the age distribution
of owner-managers in the business population as a whole. In the UK, common
age-windows for business start-ups are middle age and post-retirement (Curran et al.,
1991; Verheul and van Stel, 2010). Two-thirds of the respondents in the survey were
founders or co-founders of the business. This adds significant validity to the findings,
in that respondents were able to answer most of the questions in the survey with
authority.
Gender composition
The share of women’s self-employment in the USA has growth steadily over the past
30 years to 39 per cent, in contrast to British women’s share of self-employment, which
has hovered around 26 per cent over the past 20 years (Wilson et al., 2007, p. 155).
Although detailed aggregate data on female business ownership is inadequate,
estimates suggest that they constitute around 26 per cent of all SMEs (Carter et al.,
2001, p. 17). Over a quarter of the respondents in the sample were females, thus
ensuring a fair representation of female business owners.
Educational qualifications of business owners
Increased educational levels of business-owners have been shown to enhance their
capabilities (Barringer and Jones, 2004), although it is suggested that the benefits of
this knowledge is limited to the managerial, and not the operational roles of
business-owners (Dobbs and Hamilton, 2007). The educational levels of business
owners have also been shown to have a positive association with business performance
and growth, and the results of the survey are significant as 23.3 per cent hold a degree
or higher qualification. Professional qualifications included those that entailed an
examination or assessment such as accountants, hotel management and electrical and
civil engineers. Professional qualifications were the highest educational attainment for
7.2 per cent of owner-managers. In contrast, one in eight business owners held no
higher educational qualifications. These findings compare favourably with the
business population as a whole, where only 1 per cent of college and university
graduates are involved in enterprise (see British Venture Capital Association, 2005)
and are probably a result of the focus on larger small firms and on particular sectors.
Analysis reveals that younger business owners were more likely to have experienced
education than older owner managers.
Owner-managers’ business style
It is acknowledged that small businesses are started for a variety of reasons, depending
on the diverse motivation and management styles of managers (Delmar and Wiklund,
2008; Sambrook, 2005; Sadler-Smith et al., 2003). Owner-managers in this survey were
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14
asked to rate themselves against either/or statements that reflected their likelihood to
innovate, act opportunistically and independently, use new technologies, take risk,
become bored easily, or seek out publicity. The heterogeneity of the SME population is
displayed further in the results (Table I).
Overall, the majority of these respondents consider themselves “traditional business
owners”, “taking opportunities whenever they can”, basing decisions on “known facts”
and “retaining a low profile”. The majority of respondents also show some element of
conservatism in the use of new technologies, instead preferring to wait for systems to
be “tried and tested”. The adoption of new technologies was not associated with the
age of the owner. The results also complement the established views that business
owners have a desire for independence (Forsman, 2008) and a reluctance to plan well in
advance (Richbell et al., 2006). A relatively high percentage (43.6 per cent) classified
themselves as “restless” and “easily bored”, confirming another common
entrepreneurial trait.
Business strategy
Business planning
Advice provided to new owner-managers through textbooks, consultants and support
agencies tends to emphasise the need to plan business ventures carefully (Richbell et al.,
2006). Yet, few owners formally plan their business unless required to do so to raise
finance, and some research has cast doubts on the value of planning and improved
performance (Bridge et al., 1998) and the ability of managers to develop detailed plans
(Alpkan et al., 2007). However, other studies have linked planning to growth,
particularly after the start-up phase, with fast-growing firms being more likely to have
a business plan (Smallbone and Wyer, 2000; Mazzarol et al., 2009), or marketing plan
(Foreman-Peck et al., 2006). Whether such planning actually helps small firms develop
into larger ones, or whether it is just a characteristic they tend to adopt when they
become bigger, is less clear. The findings of this research are interesting in the context
of the conventional wisdom, whereby a significant proportion of owners claimed to
have a plan. Over 67.8 per cent claimed to have a business plan, although many (31.4
per cent) said this was informal, with 36.4 per cent answering that they had a written
plan.
We have already suggested that there are inevitable connections between how
business owners define themselves (the self definitions) and business strategy. Table II
shows that there were distinctive relationships between those businesses having a
“plan” and the respondents’ self-definitions of business style.
A breakdown of the self-definitions of management style show that those who
regard themselves as “twenty-first century entrepreneurs”, “innovative”, “using the
latest technologies” and “risk takers” are also significantly more likely to have a
business plan (Table II). Those businesses that have a plan are also more likely to be
larger and older, as are those in business and professional services and the creative
industries.
The above patterns to some extent confirm expectations that businesses
undergoing change are more likely to be following a plan. Planning also appears
more important for the larger enterprises in the sample, although it is not clear whether
this is a result of the ability to plan because of more resources, or of a greater need to
plan because of the increasing complexity of these enterprises.
42.8
I regard myself a risk taker
Note: n ¼ 360
. . . or . . .
68.1
. . . or . . .
. . . or . . .
. . . or . . .
. . . or . . .
43.6
62.2
22.8
I am restless and easily bored
I prefer to keep my head down and avoid publicity
I am happy to take high risks, providing the rewards
are high
I prefer my firm to work independently
. . . or . . .
. . . or . . .
. . . or . . .
. . . or . . .
60.3
60.0
34.2
30.3
Percentage
I am a traditional business person
I like to innovate and create change
I plan my business strategy well in advance
I use new technologies as soon as possible
Statement
I am a twenty-first century entrepreneur
I stick to what I know best
I take opportunities whenever I can
I like to wait for systems to be tried and tested before
using them
I am happy just doing my job
I am a high-profile image maker
I take decisions based on known facts so they are less
risky
I am happy to work through joint ventures and share
business with others
I prefer to avoid risks
Statement
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2.5
1.4
3.1
1.9
3.9
3.9
1.9
1.1
1.4
37.2
38.6
62.8
67.8
52.5
33.9
75.3
30.8
55.8
Percentage Neither
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Table I.
Owner-managers’
self-definitions of
business style
(percentage of
owner-managers
reporting each style of
business; multiple
responses possible)
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Table II.
Business planning:
enterprise and
owner-manager
characteristics
Characteristic
Nature of relationship with business planninga
Twenty-first century entrepreneur
Likes to innovate
Plan strategy in advance
Uses new technologies
Easily bored
Publicity seeker
Happy to take risks for rewards
Prefers to work independently
Regard myself as a risk taker
Gender
Age of owner-manager
Size of business in employment
Age of business
Sector
Positive
Positive
Positive
Positive
None
None
None
None
Positive
None
None
Positive
Positive
Varies
Note: aStatistical relationships using the x 2 test of significance (at p , 0:01)
Collaborative activity by owner-managers
As well as the evidence on owner-managers’ membership activity, we also sought to
establish the extent of strategic collaboration with other organisations. Almost six out
of ten businesses were involved in some form of external collaboration. For some,
collaboration allows the extension into new markets without the commitment of
valuable resources. For each of the activities cited, around a third of respondents were
undertaking collaboration. These findings are in contrast to some descriptions of small
business owners as isolationists who prefer to work on their own rather than seeking to
collaborate with others. When examined further, a strong relationship between
external collaboration and entrepreneurial type is revealed.
Table III summarises a range of statistically significant patterns in the data. As is
expected, those respondents who said that they were “happy to work through joint
ventures and share business with others” were much more likely to actually be
involved in external collaboration. Across all the types of collaboration there appeared
a statistical significant relationship with this self-defined business style and
collaborative behaviour. The second most important relationships were found
between the educational levels of business owners and collaborative activity. More
highly educated business owners were more likely to be involved in collaboration and
joint ventures, extending network contacts and showing good business practice.
Although the reasons for this higher level of external activity are not apparent in the
data, it is likely to be related to the networking confidence of these business owners as
a result of education and the types of businesses that they run. The results also reveal
that it is younger business owners who were much more likely to be involved in joint
ventures and the sharing of good business practice than older business owners. These
findings add further weight to the theme that younger business owners not only have
different self-definitions, but also put these into practice.
The absence of external collaboration with age of enterprise and size of enterprise
was counter-intuitive. As a business matures it may be expected that the amount of
external collaboration would increase. The analysis here shows no such relationship.
There was, however, a strong positive relationship between the employment size of the
30.3
No
Yes
No
Yesa
No
No
No
No
No
No
Yesb
No
Yes
Yes
No
No
No
Develop joint
ventures
31.1
No
No
No
No
No
No
No
Yesa
No
No
Yesb
Share workload or
customers
No
No
Yes
35.3
No
No
No
No
No
No
No
No
No
No
Yesb
Extend network
contacts
No
Yes
Yes
30.6
No
No
No
No
No
No
No
No
No
No
Yesb
Share good business
practice
No
No
Yes
43.9
No
No
No
No
Yes
No
No
No
No
No
No
Does not
collaborate
Notes: Statistical significance indicated where x 2 , 0:005; aone cell has expected count less than 5; btwo cells have expected count less than 5
Percentage of firms
Age of business
Employment size
Gender
Twenty-first century entrepreneur
Innovative
Planner
Early user of technology
Easily bored or restless
Avoid publicity
Happy to take risks if reward is high
Happy to work through joint venture and share
business with others
Risk taker
Age of respondent
Educational level
Characteristic
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Table III.
Collaborative behaviour
and owner-manager or
business characteristics
(percentage of
respondents reporting
collaborative behaviour;
multiple responses
possible)
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firm and collaboration on joint ventures. Although the data cannot identify causality, it
may suggest that firms are collaborating in order to expand. Owners seemed to be
collaborating in order to expand their customer base (e.g. through networking),
optimise their resources (e.g. by sharing workload), improve their business processes
(e.g. sharing good practice), or exploit an opportunity (e.g. joint ventures).
18
Business performance
Measurements
As has been pointed out elsewhere, measuring business performance is complex because
of the absence of tangible asset and profitability data as well as the subject nature of the
phenomenon (Wang and Ang, 2004; Achtenhagen et al., 2010). In our sample, we
expected to observe a great deal of variation in firm performance because of the different
aspirations and capabilities of the owner-managers and the market context of these
enterprises. Performance in this survey will be measured in three ways:
(1) turnover;
(2) employment growth; and
(3) profits.
Data on actual change in these measures was not obtained; rather, owner-managers
were asked to indicate the category into which their business performance fell. The
first measure of business performance examined – the value of sales in real terms over
the past year – showed the following responses:
.
grown consistently (33.9 per cent);
.
been patchy but grown overall (23.9 per cent);
.
stayed about the same (21.7 per cent);
.
been patchy but declined overall (9.4 per cent);
.
declined consistently (1.4 per cent); and
.
cannot say/in business less than three years (9.7 per cent).
Thus, the majority of the SMEs surveyed reported that between 1999 and 2002, the
value of their sales had grown consistently and only one in ten had experienced decline.
Analysis of employment changes during this time confirm some variation in
performance of the enterprises. Between 2000 and 2002, 57.1 per cent of businesses
expanded their workforce, while 31.9 per cent had stayed the same and 11 per cent had
declined. The average employment gain by each enterprise was around two people
(median 1.0, mean 2.8). A third measure of business performance, profit, showed that
74.4 per cent of businesses reported making a profit in each of the last two years.
Growing turnover and numbers employed was more commonly reported than
increases in profitability, and the proportion of enterprises not making a profit is
higher than those reporting a decline in employment or turnover. As such, profitability
appears to be the “hardest” measure of business performance.
A multivariate analysis of business performance
A range of dichotomous logit regression models were developed for the purpose of
controlling the range of determining variables affecting business performance, as
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measured by growth in employment, turnover and profits. These models sought to test
the significance of the “business style” of the owner-manager while controlling for
other key variables affecting firm growth including age of business, age of owner,
sector and size. The dependent variable takes a value of 1 if the business had grown,
and 0 otherwise. In estimating the coefficients of logit, the maximum likelihood
procedure is used. Table IV summarises the variables used in the modelling process.
These derive from the earlier discussion and are divided into “firm characteristics”,
“strategy” and “owner-manager characteristics”. The definition of each variable
describes the factors and how these are coded for this modelling.
Although the focus in the paper is on identifying statistically significant growth
models with only significant variables included, the overall general models for growth
in turnover and profits are presented, against which the parsimonious models can be
assessed (Table AI in the Appendix).
Variable name
Firm characteristics
Agebus
Size
Manuf
Consumer
Profbus
Create
Service
Strategy
Business
Market
Coljv
Small business
performance
19
Definition
Age of the business (1 ¼ 1996þ; 0 ¼ 1995 and older)
Size of business (employment) (1 ¼ 1 2 9 employees; 0 ¼ 10 þ
employees)
Manufacturing activity (1 ¼ yes; 0 ¼ no)
Consumer services (1 ¼ yes; 0 ¼ no)
Professional and business service activity (1 ¼ yes; 0 ¼ no
Creative industries (1 ¼ yes; 0 ¼ no
Retail, hotels and restaurants and consumer services (1 ¼ yes; 0 ¼ no)
Existence of a written business plan (1 ¼ yes; 0 ¼ no)
Existence of a marketing budget (1 ¼ yes; 0 ¼ no)
Business has undertaken collaborative joint ventures (1 ¼ yes;
0 ¼ no)
Owner-manager characteristics
Ageown
Age of the owner-manager (1 ¼ 40 years or less; 0 ¼ 40þ years)
Gender
Gender of the owner-manager (1 ¼ male; 0 ¼ female)
Educ
Highest educational achievement of the owner-manager (1 ¼ degree
and above; 0 ¼ not)
Enttype
Owner-manager a “twenty-first century entrepreneur” (1 ¼ yes;
0 ¼ no)
Innovate
Owner-manager “likes to innovate and create change” (1 ¼ yes;
0 ¼ no)
Planner
Owner-manager “likes to plan strategy in advance” (1 ¼ yes; 0 ¼ no)
Technol
Owner-manager “uses new technology as soon as possible” (1 ¼ yes;
0 ¼ no)
Restless
Owner-manager becomes “restless and easily bored” (1 ¼ yes; 0 ¼ no)
Publicit
Owner-manager is “high profile image maker” (1 ¼ yes; 0 ¼ no)
Risks
Owner-manager is “happy to take risks, providing the rewards are
high” (1 ¼ yes; 0 ¼ no)
Indept
Owner-manager is “happy to work through joint ventures and share
business with others” (1 ¼ yes; 0 ¼ no)
Risktake
Owner-manager regards themselves a risk taker (1 ¼ yes; 0 ¼ no)
Table IV.
Definition of variables
used in the logit analyses
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20
The first regression results in Table V relate to the dichotomous logit model for
employment growth. In this model, employment growth (the dependent variable) takes
a value of 1 if the business has grown over the previous two years and 0 otherwise. The
explanatory (or independent) variables having the greatest effect on employment
growth are shown together with the conventional statistical measures. In estimating
the coefficients of logit, the maximum likelihood procedure is used. In presenting the
results we have reported the coefficient values and the odds ratios. Interpreting logit
regression output in terms of odds rather than probabilities confers certain advantages.
Most important among these is that exp(b) is a single summary statistic for the partial
effect of a given predictor on the odds, controlling for other predictors in the model.
Logit is simply the log of the odds of being in one versus another category of the
dependent variable. The odds ratio associated with each coefficient is presented in
Table V. The odds ratio is a multiplicative coefficient, which means that “positive”
effects are greater than 1 while “negative” effects lie between 0 and 1. The odds ratio is
the number by which one would multiply the odds of a business experiencing
employment growth for each one-unit increase in the independent variable. An odds
ratio greater than 1 indicates that the odds of a business recording employment growth
increases when the independent variable increases. An odds ratio of less than 1
indicates that the odds of a business growing in employment terms decreases when the
independent variable increases, while estimates close to 1 indicate no effect on the
odds. Table V presents the estimated odds ratios associated with the different
explanatory variables. The x 2 statistic for the joint impact of all the explanatory
variables on the dependent variable is significant.
The results show that younger SMEs (established after 1995) and the existence of a
written business plan are positively and significantly associated with growth in
employment over the previous two years. This reflects the findings of earlier studies
that view planning to have a positive impact on growth (e.g. Richbell et al., 2006), but
counters the findings of others who view formal planning as being less important in
firm performance (e.g. Lyles et al., 1993; Fletcher and Harris, 2002). Clearly, more
research is needed on the type of planning and business growth in SMEs. As we saw
earlier, the existence of a business plan is positively associated with those having, what
could be considered, a dynamic business style and in particular, “twenty-first century
entrepreneurs”, “risk takers”, “innovators” and “willingness to use new technologies”.
The odds ratio of this variable is positive and exceeds 1.
On the other hand, the odds ratios of size of business and sector in relation to
performance are less than one. This suggests that there is a negative and significant
relationship between growth and business size with larger firms (ten or more
employees) growing slower in employment terms than firms employing 5-9 employees.
This finding is consistent with the literature, which suggests that smaller firms are
more flexible than larger firms, as they are able to seize new opportunities quickly,
where the owner-manager is closer to the market (Escribá-Esteve et al., 2008; Steffens
et al., 2009). Finally, controlling for sector reveals that there is a negative and
significant relationship with businesses involved in manufacturing compared to
retailing, hotels and restaurants and consumer services. In other words, controlling for
size and age of business, firms in manufacturing have been growing slower than their
counterparts in other sectors.
0.10
x 2 ð18Þ ¼ 49:63
0.0001
2223.11
0.10
360
0.03
0.64 * *
0.11
1.03
1.89
1.11
1.19
1.07
1.15
0.95
0.87
0.81
0.81
1.14
1.06
21.24 * * *
x 2 ð4Þ ¼ 11:90
0.04
2224.56
0.03
360
0.29
1.34
–
1.64
–
–
–
–
–
–
–
Profits
1.33 * * *
x 2 ð4Þ ¼ 6:66
0.08
2201.28
0.02
360
–
–
–
–
–
–
–
–
–
–
–
–
–
–
20.10
20.63 * *
0.11
Coefficient
–
–
–
–
–
–
–
–
–
–
–
–
–
–
0.90
0.53
1.12
Odds ratio
Notes: We utilise three main measures of business performance including, employment change over the previous two years (2000-2002); turnover change for the
previous three years (in real terms, 1999-2002); and profitability (whether or not the business had made profits over each of the previous two years). *denotes
significance at the 0.10 level; * *denotes significance at the 0.05 level; * * *denotes significance at the 0.01 level
Constant
x2
Prob . x 2
Log likelihood
Pseudo-R 2
n
Strategy
Market
Business
Coljv
0.18
0.07
0.14
20.05
20.15
20.21
20.21
0.13
0.06
Entrepreneurial traits
Twenty-first century entrepreneur
Innovate
Planner
Technol
Restless
Publicit
Risks
Indept
Risktake
–
0.50 * *
–
–
–
–
–
–
–
–
–
–
20.06
0.15
20.13
–
–
–
1.20
0.18
Owner-manager characteristics
Gender
Ageown
Educ
0.95
1.17
0.88
1.24
0.90
2.580
0.58
0.56
0.22
20.11
0.95 * * *
20.55 * *
20.57 * *
Turnover growth
Coefficient
Odds ratio
Firm characteristics
Agebus
Size
Manuf
Consumer
Employment Growth
Coefficient
Odds ratio
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Small business
performance
21
Table V.
Logit regression models
of employment growth,
turnover growth and
profits
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22
The second set of regression results in Table V presents the equation with the greatest
explanatory power for turnover grow thover the previous three years (see the
Appendix for the general logit model for turnover growth). The importance of an
“innovating” owner-manager overshadowed all others. Owner-managers who
considered themselves to be “innovative and creating change” (controlling for size,
sector and age of business) were 1.6 times more likely to run businesses that
experienced turnover change. Other factors were also important in contributing to the
overall significance of the model, including larger firms, younger firms, those in
consumer services and those having a written business plan. However, these variables
were not statistically significant within the model.
A final measure of business performance is whether the business had made a profit
in each of the last two years, and this is the third set of regression results that are
reported in Table V. In this case it is firms that are smaller, older and in sectors other
than consumer services that show the greater odds of being profitable. This
parsimonious model, along with the previous ones, therefore confirms the widespread
view that size and age of enterprise are important when seeking to understand the
performance of the enterprise (see the Appendix for the general logit model for profits).
Profitability is most strongly associated with smaller, older businesses. This reinforces
the notion that the owners who develop the most profitable businesses are those who
are content to grow their businesses at a steady, unspectacular rate over a relatively
long period. This is an important finding, as it contributes to more critical debates on
growth that have argued that not all firms benefit from the promotion of sustainable
growth (St-Jean et al., 2008; Storey, 2011). Furthermore it has been argued elsewhere
that firms that develop innovative products and become profitable first, before seeking
growth, are more likely to experience growth beyond the short term (Davidsson et al.,
2009; Steffens et al. 2009). Although the age of business owner does not emerge in this
analysis, it should be noted that there was a very strong correlation between the age of
the enterprise and the age of the business owner in the sample dataset.
Conclusions
This paper seeks to contribute to the development of the literature on factors that
influence the performance of businesses through a robust empirical study. It focused
on SMEs that employed between five and 249 people on the justification that these
enterprises have displayed growth and are more likely to contribute to the economy.
Our definitions of business performance included changes in employment, financial
turnover and profits. The analysis began by setting out the increasingly accepted
three-fold classification of the characteristics that, a priori, influence growth –
i.e. business characteristics, owner-manager characteristics and business strategy, as
established by Storey (1994).
Logit models were used to investigate relationships between the performance of the
business, the characteristics of the business, the profile of the owner and business
strategy. The modelling revealed that older, smaller businesses, with a written
business plan, in consumer services and run by owners who consider themselves to be
innovative, were more likely to have experienced higher turnover and employment
growth. This adds support to the importance of SME planning to manage resources
during growth (Richbell et al., 2006; Mazzarol et al., 2009). However, younger
businesses were more likely to be profitable. Owners who develop the most profitable
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businesses seem to be those who are prepared to grow their businesses at a steady,
unspectacular rate over a relatively long period, reflecting the work of Davidsson et al.
(2009). The model on employment growth displayed the highest level of statistical
significance. These findings contribute to more critical studies that have stressed the
discontinuous, sporadic nature of growth (Blackburn et al., 2009; Storey, 2011), and by
complementing the work of St-Jean et al. (2008), who highlight how the difficulties of
managing internal change can impede growth. Subsequently, it may be suggested that
slower growth is more sustainable and manageable for owner managers, in comparison
to the rarely unobtainable high growth favoured by policy-makers and the media.
As was expected, factors relating to business characteristics, owner-manager
characteristics and business strategy can all be important in understanding small firm
growth (e.g. Storey, 1994; Dobbs and Hamilton, 2007; Barbero et al., 2011; Hamilton, 2012;
Hansen and Hamilton, 2011). However, the analysis set out to assess the influence of a
specific aspect of the characteristics of the owner-manager, namely that of “business
style”, building on the work of Sadler-Smith et al. (2003). Using a series of respondent
self-defined “types” or “business styles”, it emerged that these were an important addition
to the range of variables normally associated with business performance. Indeed, in the
case of turnover growth, the presence of an owner-manager who considered themselves
an “innovator” or “creator of change” increased the likelihood of growth substantially.
The implications of these results underline the complexity of small firm growth, as
highlighted in recent debates (Barringer et al., 2005; Coad, 2009; Storey, 2011) and pose
a challenge for those seeking to theorise this phenomenon. The paper demonstrates
that there are clear structural constraints on small firm growth (age, size, and sector)
that combine with some strategic factors and other personal factors that are
notoriously difficult to measure to produce different performance outcomes. An
important conclusion to emerge from the analysis is that there is a broad confirmation
of the validity of established theoretical constructs that govern our understanding of
firm growth. In other words, whilst owner-manager characteristics and business style
are important, it appears that the structural conditions within which the enterprise
operates strongly determines its performance. However, the paper also demonstrates
that although contributing to the knowledge base, our understandings of business
performance and levels of theorising remain incomplete. How we measure performance
is also critical. Indeed, our results showed differences according to the particular
measurements of performance used (i.e. employment, turnover, or profits), and we
should encourage scholars to realise the limitations of singular measures. How
advocates of business support strategies might respond to this complexity also
remains a challenge for those engaged in the design and delivery of public policy to
promote SME performance.
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Small business
performance
Appendix
Turnover growth
Coefficient
Odds ratio
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Firm characteristics
Agebus
Size
Manuf
Profit growth
Coefficient
Odds ratio
0.24
2 0.11
0.26
1.27
0.24
1.30
2 0.57 *
0.15
2 0.19
0.57
1.16
0.83
Owner-manager characteristics
Gender
0.38
Ageown
2 0.07
Educ
0.34
1.47
0.93
1.40
0.07
2 0.22
2 0.38
1.08
0.81
0.69
Entrepreneurial traits
Enttype
Innovate
Planner
Technol
Restless
Publicit
Risks
Indept
Risktake
0.30
0.48 * *
2 0.25
2 0.02
2 0.16
0.06
2 0.04
0.20
2 0.06
1.35
1.61
0.78
0.98
0.85
1.06
0.96
1.22
0.79
2 0.01
0.21
2 0.14
2 0.62 * *
0.27
0.23
2 0.10
0.03
2 0.08
0.99
1.23
0.87
0.54
1.31
1.26
0.90
1.03
0.92
Strategy
Market
Business
Coljv
2 0.16
0.20
2 0.02
0.85
1.22
0.98
2 0.13
0.08
0.01
0.88
1.08
1.00
Constant
x 2(18)
Prob . x 2
Log likelihood
Pseudo R 2
n
2 1.56 * *
20.29
0.32
2 220.36
0.04
360
1.49 * *
21.57
0.25
2 193.83
0.05
360
Notes: *denotes significance at the 0.10 level; * *denotes significance at the 0.05 level; * * *denotes
significance at the 0.01 level
Corresponding author
Robert A. Blackburn can be contacted at: r.blackburn@kingston.ac.uk
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27
Table AI.
General logit models of
turnover growth and
profit growth
This article has been cited by:
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performance: the mediating role of entrepreneurial orientation. Small Business Economics . [CrossRef]
2. 2014. Ten top tips for small to medium enterprise (SME) success. Strategic Direction 30:2, 14-17.
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