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GROWTH, EXPORTING AND INNOVATION IN MANUFACTURING SMEs:
EVIDENCE FROM AUSTRALIA’S BUSINESS LONGITUDINAL SURVEY
Professor Richard G.P. McMahon,
Head, School of Commerce,
The Flinders University of South Australia,
GPO Box 2100,
Adelaide South Australia 5001.
Telephone: +61 8 82012840
Facsimile: +61 8 82012644
Email: Richard.McMahon@flinders.edu.au
SCHOOL OF COMMERCE
RESEARCH PAPER SERIES: 00-10
ISSN: 1441-3906
Acknowledgments
Permission from the Australian Statistician to use confidentialised data from the federal
government’s Business Longitudinal Survey is gratefully acknowledged. Responsibility for
the findings of this research lies solely with the author.
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GROWTH, EXPORTING AND INNOVATION IN MANUFACTURING SMEs:
EVIDENCE FROM AUSTRALIA’S BUSINESS LONGITUDINAL SURVEY
Abstract
Two broad hypotheses are examined in this paper. The first is that, in small and
medium-sized enterprises (SMEs), linkages exist between growth, exporting and
innovation that are statistically significant and persistent over time. Overall support is
found for this hypothesis. The second hypothesis examined is that knowledge of
exporting and innovation behaviour can be reliably used to anticipate SME growth
potential for research and policy purposes. Support for this hypothesis is less
compelling.
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INTRODUCTION
A broad definition of a growth SME (small or medium-sized enterprise) suggested by
McMahon et al. (1993, p. 15) is as follows:
In general terms, a smaller growth enterprise is considered to be an owner-managed
concern experiencing on-going, significant and often rapid increases in some or all of
the usual indicators of size such as sales revenues, assets, profits (possibly) and number
of employees; and which may also be moving towards greater product, geographical or
technological diversity.
This definition does not equate growth with just increases in enterprise size, however
measured. Greater diversity of operations – for example, arising from internationalisation
and/or innovation – is seen as a concomitant with growth. Reference to greater geographical
diversity posits a linkage between SME growth and export development as a growth strategy.
Reference to greater technological diversity posits a further linkage between SME growth and
technological innovation as a growth strategy.
A report by McKinsey & Company (1994, pp. vii-viii) to the Australian Manufacturing
Council reinforces the impression of important linkages between manufacturing SME
growth, exporting and innovation:
Our aim . . . has been to understand the nature of the relationships or linkages that are
important for sustaining the growth of our manufacturing exporters – relationships that
drive successful innovation and performance improvement.
. . . exporting and innovativeness are closely intertwined. We do not know in which
direction the causation goes but innovative firms are more likely to export, and
exporting provides opportunities, especially in gaining access to ideas, which are
essential for innovativeness. Government policy that aims to enhance both exporting
and innovativeness is mutually reinforcing. Push on one and the economy also gets the
advantage of the other. Encouraging firms to export might well be the single best
measure to stimulate innovation in Australian manufacturing.
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The recent availability of data from Australia’s Business Longitudinal Survey (BLS) provides
a promising new opportunity to explore the linkages so identified.
This paper builds upon a study previously undertaken by the author (McMahon,
forthcoming) as part of an on-going research effort to derive, characterise and employ an
empirically-based development taxonomy for SMEs operating as proprietary companies in
the manufacturing sector, using panel data now available from the BLS. The principal
objective in the paper is to examine the existence, persistence and usefulness of conjectured
linkages between SME growth, exporting and innovation amongst Australian manufacturers.
The paper proceeds as follows. After briefly outlining key findings of the author’s previous
study, and of some prior research on growth, exporting and innovation amongst Australian
SMEs, the current research method is outlined. Thereafter, findings of the research are
presented, followed by conclusions arising from this investigation.
PRIOR RESEARCH
SME Growth
In the author’s previous research (McMahon, forthcoming), exploratory cluster analysis
was used with key enterprise age, size and growth variables to discover if there appear to be
any stable development pathways evident in the BLS panel data. Each of four annual data
collections for the on-going longitudinal panel of 871 manufacturing SMEs was separately
examined using cluster analysis. Comparisons were then made of cluster analysis outcomes
over time. Using the clusters as markers or signposts, three relatively stable SME
development pathways were discernible in the longitudinal panel results – low, moderate and
high growth. The low growth development pathway appears to account for approximately 70
per cent of SMEs in the panel. The moderate growth pathway seems to be followed by
roughly 25 per cent of the panel. And around 5 per cent of the panel look to lie on the high
growth pathway, which is in accord with the observed rarity of substantial growth amongst
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SMEs world-wide (McMahon et al., 1993). Differences between the identified SME
development pathways in terms of enterprise age, size and growth variables are highly
significant in a statistical sense, thus underpinning confidence in the development taxonomy.
It would appear that the development pathways and the pace of SME development
(over 20 years or so) in the McMahon (forthcoming) study match reasonably well with those
in earlier research of a similar nature undertaken by Hanks et al. (1993). Both development
models seem to lead towards the same range of SME configurations that are widely
recognised in the relevant research literature (McMahon et al., 1993):
 Traditional SMEs – following the low growth development pathway, these concerns
generally have few, if any, growth aspirations. They principally exist to provide their
owner-managers with a source of employment and income. Furthermore, they are
frequently operated in a manner consistent with the life-style aspirations of their ownermanagers. The McMahon (forthcoming) study suggests that after approximately 15
years such SMEs would have fewer than 20 employees, sales less than $3 million per
annum, total assets below $2 million, little or no employment growth, and sales growth
up to 5 per cent per annum.
 Capped growth SMEs – following the moderate growth development pathway, these
concerns generally have modest growth aspirations. Bounds to growth could be
externally imposed by the nature of their competitive environment; or may be intrinsic
given the nature of their operations. Frequently though, growth is deliberately capped
by owner-managers to a rate that limits dependence upon external financing – thus
minimising surrender of control and accountability obligations this support would
normally bring. The McMahon (forthcoming) study suggests that after approximately
15 years such SMEs would have fewer than 100 employees, sales around $10 million
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per annum, total assets less than $10 million, employment growth up to 3 per cent per
annum, and sales growth as much as 10 per cent per annum.
 Entrepreneurial SMEs – following the high growth development pathway, these
concerns generally have ambitious growth aspirations. They are most often associated
with entrepreneurial aptitude, international outlook, technical and commercial
innovation, and other business qualities that could see them eventually become large
enterprises. The McMahon (forthcoming) study suggests that after approximately 15
years such SMEs would have over 100 employees, sales around $30 million per annum,
total assets more than $20 million, employment growth exceeding 5 per cent per
annum, and sales growth greater than 10 per cent per annum.
The fact that these common SME configurations are recognised in the research lends further
plausibility to the empirically-based development taxonomy derived.
SME Growth, Exporting and Innovation
Predating the recent phenomenon of ‘born global’ SMEs, Welch (1977, p. 3) places the
internationalisation of businesses within the context of their broader growth aspirations as
follows:
The international growth of the firm should be viewed as part of the overall growth
process of the firm, initially growing out of its domestic activities but remaining
inextricably entwined with them. Internationalisation undoubtedly adds a new
dimension to the firm’s total operations but it builds on and interacts with total
expansion. As a consequence, international decisions are not simply explained by what
happens within foreign markets.
Subsequent support for this position is provided by Vozikis & Mescon (1988), Kamath et al.
(1987) and McAuley (1988) amongst other researchers.
A recent report from the Australian federal government (Department of Foreign Affairs
and Trade, 1995, p. 4) points out that:
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Most SMEs . . . are globalised only to a limited extent, and are best described as being
internationalised. An SME exporting to one or two countries in the region would not
consider itself to be globalised, although it is clearly engaged in international activity.
Another key report on internationalised SME in the same year observes that (Australian
Manufacturing Council, 1995, p. 11):
Some of the firms . . . export only 8 to 10 per cent of their sales. In the past we have
called such exporters opportunistic, arguing that a firm had to export 20 per cent of
sales to be considered a strategic or serious exporter. However, this distinction is
inappropriate when small-scale exporters produce global products. The learning
opportunities gained by being a player (even a small player) in the international
economy are the real advantage that exporting provides.
This research adopts the latter, broader view on the significance of SME exporting.
Innovation refers to creation of commercial value through introduction of new or
improved products or processes (Australian Manufacturing Council, 1995). Linkages
between SME growth, exporting and innovation constitute a major theme in a number of
significant reports to or from governmental/quasi-governmental organisations in Australia
during the early to mid-1990s. They include the Emerging Exporters report (McKinsey &
Company, 1993), the Small Business Innovation report (Bureau of Industry Economics,
1994), the Wealth of Ideas report (McKinsey & Company, 1994), the Innovation Cycle report
(Australian Manufacturing Council, 1995), and the Winning Enterprises report (Department
of Foreign Affairs and Trade, 1995). These place a great deal of emphasis, if not complete
focus, upon manufacturing SMEs.
On the linkage between SME growth and innovation, the Small Business Innovation
report (Bureau of Industry Economics, 1994, p. 23) points out that:
Innovations may be used as a strategy for growth or survival. Growth may be achieved
if innovation enables the expansion of existing markets or entry into new markets. On
the other hand, firms may be forced to match the innovation of rivals to maintain
market share.
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On the linkage between SME innovation and exporting, the Emerging Exporters report
(McKinsey & Company, 1993) identifies four ways in which technological innovation can
help to create competitive advantage in international markets:
 The initial success of ‘born global’ SMEs is often based on technologically unique
products.
 In order to internationalise their operations, SMEs already established in domestic
markets usually need to develop new products tailored to the demands of export
markets.
 Once established in international markets, SMEs need to engage in continuous product
and process innovation in order to enjoy on-going success.
 SMEs exploiting niche overseas markets inevitably face sales ceilings, and so need to
innovate in order to enter new niches and continue to grow.
The Emerging Exporters report (McKinsey & Company, 1993) indicates that 44 per cent of
emerging exporters growing at a rate greater than 15 per cent per annum developed new
products for export. Of emerging exporters growing at less than 15 per cent per annum, only
17 per cent developed new products for export.
The Emerging Exporters report (McKinsey & Company, 1993) also reveals that most
emerging exporters develop new technologies and products in-house (that is, undertake their
own research and development). An appropriate perspective on this finding is provided by the
Small Business Innovation report (Bureau of Industry Economics, 1994, p. 5):
R&D is only one of the ways in which firms can acquire the knowledge required to
introduce a technical innovation – information can also be obtained from parent firms,
by licensing, by purchase, by accessing publicly available information and so on – but
it is the route on which innovation policy in Australia and many other countries focus.
The Wealth of Ideas report (McKinsey & Company, 1994) and the Winning Enterprises
report (Department of Foreign Affairs and Trade, 1995) both strongly reflect this perspective.
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Finally, the case for a linkage between SME exporting and innovation is put most
persuasively by the Innovation Cycle report (Australian Manufacturing Council, 1995, pp. 56) as follows:
Of all the variables that we examined, in terms of both practices and outcomes, that
which most differentiates innovative firms from the rest is exporting. Innovative firms
are much more likely to export. They can compete against the rest of the world.
Exporting returns to firms more than just the value of their sales. It puts them out in the
most competitive market places where there is the greatest pressure to improve
performance. The pressure on firms to improve is balanced by their enhanced capacity
to deliver. This capacity is provided by access to new customers, a wide range of
information and exposure to new ideas. Some of the additional capacity is provided by
the linkage relationships that exporting develops.
The Wealth of Ideas report (McKinsey & Company, 1994) and the Winning Enterprises
report (Department of Foreign Affairs and Trade, 1995) explain the significance of the
‘linkage relationships’ alluded to at the close of this quotation. They most often entail close
collaboration with technologically demanding foreign customers that may result in sharing of
the costs and risks of innovation. They may also extend to privileged access to foreign
research and development resources and technological infrastructure.
The central message for the current research from the reports reviewed above is clear
and unambiguous. However, notwithstanding their many merits, none of these reports
actually demonstrate, using appropriate statistical analysis of large-scale representative
samples, the existence, persistence and usefulness of the conjectured linkages between SME
growth, exporting and innovation amongst Australian manufacturers. Thus, the two broad
hypotheses to be tested in the remainder of this paper are as follows:
H1: That linkages between growth, exporting and innovation exist amongst Australian
manufacturing SMEs, that they are statistically significant, and that they persist
over time.
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H2: That knowledge of exporting and innovation behaviour amongst Australian
manufacturing SMEs can be reliably used to anticipate their growth potential for
(inter alia) research and government support purposes.
RESEARCH METHOD
The panel data employed in this research are drawn from the BLS conducted by the
Australian Bureau of Statistics (ABS) on behalf of the federal government over the four
financial years 1994-95 to 1997-98. Costing in excess of $4 million, the BLS was designed to
provide information on growth and performance of Australian employing businesses.
The ABS Business Register was used as the population frame for the survey, with
approximately 13,000 business units being selected for inclusion in the 1994-95 mailing of
questionnaires. For the 1995-96 survey, a sub-sample of the original selections for 1994-95
was chosen, and this was supplemented with a sample of new business units added to the
Business Register during 1995-96. The sample for the 1996-97 survey was again in two parts.
The first formed the longitudinal or continuing part of the sample, comprising all those
remaining live businesses from the 1995-96 survey. The second part comprised a sample of
new business units added to the Business Register during 1996-97. A similar procedure was
followed for the 1997-98 survey. Approximately 6,400 business units were surveyed in each
of 1995-96, 1996-97 and 1997-98. The BLS did not employ completely random samples. The
original population (for 1994-95) was stratified by industry and business size, with equal
probability sampling methods being employed within strata. Further stratification by
innovation, exporting and growth status took place for the 1995-96 survey.
Data collection in the BLS was achieved through self-administered, structured
questionnaires containing essentially closed questions. Copies of the questionnaires used in
each of the four annual collections can be obtained from the ABS. Because information
collected in the BLS was sought under the authority of the Census and Statistics Act 1905,
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and thus provision of appropriate responses to the mailed questionnaires could be legally
enforced by the Australian Statistician, response rates were very high by conventional
research standards – typically exceeding 90 per cent.
The specific BLS data used in this study are included in a Confidentialised Unit Record
File (CURF) released by the ABS on CD-ROM in December, 1999. This CURF contains data
on 9,731 business units employing fewer than 200 persons – broadly representing SMEs in
the Australian context. Restricted industrial classification detail, no geographical indicators,
presentation of enterprise age in ranges, and omission of certain data items obtained in the
BLS all help to maintain the confidentiality of unit records.
This research is concerned only with manufacturing SMEs in the BLS CURF,
representing approximately 35 per cent of businesses in the file. Additional focus is provided
by considering only manufacturing SMEs legally organised as proprietary companies.
Approximately 71 per cent of manufacturing SMEs in the file are proprietary companies.
Variables used in this research are either categorical in nature or, if metric, have
irregular distributional properties. Thus, non-parametric/distribution free techniques of
statistical analysis are employed exclusively.
RESEARCH FINDINGS
Existence of SME Growth, Exporting and Innovation Linkages
The exporting and innovation behaviour of manufacturing SMEs in the study are
initially captured in a series of dichotomous variables as follows:
 Exporter status – whether or not the businesses exported goods in each of the four years
in the longitudinal panel.
 Innovator status – whether or not the businesses developed or introduced any new or
substantially changed products or services in each of the four years in the longitudinal
panel.
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 Exporter and innovator status – whether or not the businesses both exported goods and
developed or introduced any new or substantially changed products or services in each
of the four years in the longitudinal panel.
Frequency distributions for these variables across low, moderate and high growth
development pathways identified amongst these manufacturing SMEs by McMahon
(forthcoming) are presented in Table 1.
Inspection of Table 1 reveals that approximately 30 to 40 per cent of SMEs on the low
growth pathway report export sales. This compares with around 55 to 60 per cent of
businesses on the moderate growth pathway, and roughly 60 to 70 per cent of those on the
high growth pathway. Hence, exporting appears to be more prevalent amongst higher growth
concerns. Approximately 20 to 40 per cent of SMEs on the low growth pathway appear to be
innovators. This compares with around 30 to 50 per cent of businesses on the moderate
growth pathway, and roughly 40 to 60 per cent of those on the high growth pathway. Here,
innovation appears to be more prevalent amongst higher growth concerns. Finally,
approximately 10 to 20 per cent of SMEs on the low growth pathway report being both
exporters and innovators. This compares with around 20 to 30 per cent of businesses on the
moderate growth pathway, and roughly 30 to 40 per cent of those on the high growth
pathway. Thus, being both an exporter and an innovator appears to be more prevalent
amongst higher growth concerns.
Further evidence for the existence of linkages between SME growth, exporting and
innovation in the study sample is provided by examining a series of metric variables
reflecting the extent of exporting or innovation activities as follows:
 Export intensity – the percentage of total sales accounted for by export sales in each of
the four years in the longitudinal panel.
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 Research and development commitment – expenditure on research and development
expressed as a percentage of total sales in each of the four years in the longitudinal
panel.
 Innovation commitment – total expenditure on innovation (including research and
development, training staff, acquisition of patents/trademarks/licences, tooling up,
industrial engineering, manufacturing start-up, and marketing new products) expressed
as a percentage of total sales in three of the four years in the longitudinal panel (total
innovation expenditure is not available for 1995-96).
Certain statistics (mean, standard deviation and coefficient of variation) for these variables
across low, moderate and high growth SME development pathways are presented in Table 2.
Inspection of Table 2 reveals that export intensity is approximately 5 per cent for SMEs
on the low growth pathway. This compares with around 8 per cent for businesses on the
moderate growth pathway, and roughly 9 per cent for those on the high growth pathway.
Hence, export intensity appears to be higher amongst higher growth concerns. Notice also
that variability in export intensity seems to decrease for higher growth concerns. Research
and development commitment is approximately 1.2 per cent for SMEs on the low growth
pathway. This compares with around 0.7 per cent for businesses on the moderate growth
pathway, and roughly 0.6 per cent for those on the high growth pathway. Here, the relative
commitment to research and development appears to be lower amongst higher growth
concerns. Of course, the absolute commitment to research and development in dollar terms is
likely to be higher for higher growth concerns. Variability in relative commitment to research
and development seems to decrease for higher growth concerns. Finally, innovation
commitment is approximately 1.9 per cent for SMEs on the low growth pathway. This
compares with around 1.5 per cent for businesses on the moderate growth pathway, and
roughly 1.1 per cent for those on the high growth pathway. Thus, the relative commitment to
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innovation appears to be lower amongst higher growth concerns. As with research and
development, the absolute commitment to innovation in dollar terms is likely to be higher for
higher growth concerns. Variability in relative commitment to innovation seems to decrease
for higher growth concerns.
Statistical Significance of SME Growth, Exporting and Innovation Linkages
Having established that linkages do seem to exist between growth, exporting and
innovation amongst manufacturing SMEs in the study sample, it is now appropriate to
determine whether these linkages appear to be statistically significant.
Initially, the statistical significance of relationships between the exporter, innovator,
and exporter and innovator status variables across low, moderate and high growth
development pathways can be examined. This is done using 2 tests in Table 3. It is clear that
highly statistically significant relationships do exist between the exporter status and innovator
status variables in each of the four years in the longitudinal panel. The evidence is that
exporting SMEs are more than likely to also be innovators.
Focusing on the exporting linkage with SME growth, over the four years in the
longitudinal panel highly statistically significant relationships exist between the exporter
status variables and the variable indicating SME development pathways. Higher growth
manufacturing SMEs are more than likely to also be exporters. The statistical significance of
the relationship between the innovator status variables and the variable indicating SME
development pathway is more equivocal. In two of the four years in the longitudinal panel the
relationship is not significant; whereas in the other two years the relationship is significant.
Amongst other things, this suggests that innovation is a less significant and/or less consistent
concomitant with SME growth than exporting. Finally, the relationship between the exporter
and innovator status variables and the variable indicating SME development pathways is
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highly statistically significant in all four years in the longitudinal panel. Higher growth
manufacturing SMEs are more than likely to also be both exporters and innovators.
Now, a series of Kruskal-Wallis one-way analysis of variance tests involving variables
reflecting the extent of exporting or innovation activities can be examined. These are
presented in Table 4. First, Kruskal-Wallis tests lead to rejection of null hypotheses that
median values for research and development commitment do not differ between nonexporters and exporters over the four years in the longitudinal panel. Kruskal-Wallis tests
also lead to rejection of null hypotheses that median values for innovation commitment do
not differ between non-exporters and exporters over the four years in the longitudinal panel.
Both research and development commitment and innovation commitment are found to be
higher amongst exporting SMEs. Further Kruskal-Wallis tests lead to rejection of null
hypotheses that median values for export intensity do not differ between non-innovators and
innovators over the four years in the longitudinal panel. Export intensity is found to be higher
amongst innovating SMEs. Together, the three series of tests support the earlier finding of a
highly statistically significant relationship between SME exporting and innovation.
Focusing on the exporting linkage with SME growth, Kruskal-Wallis tests lead to
rejection of null hypotheses that median values for export intensity do not differ between
development pathways. Export intensity is found to be higher amongst higher growth
manufacturing SMEs. As before, the statistical significance of the relationship between
innovation and SME development pathway is more equivocal. In two of the four years in the
longitudinal panel, Kruskal-Wallis tests lead to acceptance of null hypotheses that median
values for research and development commitment do not differ between development
pathways. Furthermore, in two of three years in the longitudinal panel, Kruskal-Wallis tests
lead to acceptance of null hypotheses that median values for innovation commitment do not
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differ between development pathways. Again, the suggestion is that innovation is a less
significant and/or less consistent concomitant with SME growth than exporting.
Persistence of SME Growth, Exporting and Innovation Linkages
It is now appropriate to ascertain whether linkages that exist between growth, exporting
and innovation amongst manufacturing SMEs in the study sample appear to persist over time.
If they are found to be persistent, this lends further support to the contention that such
linkages are sufficiently important to warrant further attention from researchers and policymakers in the field.
While the data and analyses presented so far in the paper may suggest the persistence of
linkages between growth, exporting and innovation amongst the manufacturing SMEs
studied, this impression only applies to the businesses in aggregate. What is sought is an
indication of whether there seems to be continuity of the linkages at the individual business
level over the four years of the longitudinal panel. This is gained by examining the results of
a series of Friedman two-way analysis of variance tests presented in Table 5. Consider first
the stability of the exporter status variables over time across low, moderate and high growth
development pathways. For both moderate and high growth SMEs, it is not possible to reject
null hypotheses that exporter status is the same over the four years of the longitudinal panel.
It is, however, possible to reject such a null hypothesis for low growth SMEs. The suggestion
here is that individual businesses following the low growth development pathway tend to
change exporter status over time; whereas this is not the case for manufacturing SMEs on the
moderate and high growth development pathways. This is consistent with the earlier claim
that many smaller SMEs are simply opportunistic exporters. It would appear that more
regular exporting activity may be required in order to follow higher growth development
pathways.
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Now consider the stability of the innovator status variables over time across low,
moderate and high growth development pathways. For all three pathways, it is possible to
reject null hypotheses that innovator status is the same over the four years of the longitudinal
panel. The suggestion here is that, regardless of their growth aspirations, individual
businesses tend to change innovator status over time. This reinforces the earlier impression
that innovation is a less significant and/or less consistent concomitant with SME growth than
exporting. The stability of the exporter and innovator status variables over time across low,
moderate and high growth development pathways is only marginally greater. Only for high
growth SMEs is it not possible to reject the null hypothesis that exporter and innovator status
is the same over the four years of the longitudinal panel. Thus, it would appear that more
regular exporting and innovation activity may be required in order to follow the high growth
development pathway.
It remains to examine the stability over time of variables reflecting the extent of
exporting or innovation activities. For all three development pathways, it is not possible to
reject null hypotheses that export intensity is the same over the four years of the longitudinal
panel. The suggestion here is that, regardless of their growth aspirations, individual
businesses tend not to change their relative dependence on export versus domestic sales over
time. In other words, the relative importance of exporting does not seem to change regardless
of the development pathway being followed. Could it be that manufacturing SMEs in the
study sample undertake a certain level of exporting consistent with their growth aspirations,
and then simply maintain that degree of commitment to international activity? Perhaps there
is a ‘comfort zone’ in terms of relative dependence on export sales that SMEs choose to be in.
If so, policy initiatives to increase the number of SMEs exporting are more likely to be
effective than efforts to increase the level of exporting amongst those concerns that have
already taken a measured plunge into international business.
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Consider now the stability of the research and development commitment variables over
time across low, moderate and high growth development pathways. For both low and
moderate growth SMEs, it is possible to reject null hypotheses that research and development
commitment is the same over the four years of the longitudinal panel. However, it is not
possible to reject such a null hypothesis for high growth SMEs. A more consistent
commitment to research and development may be required in order to follow the high growth
development pathway. Finally, consider the stability of the innovation commitment variables
over time across low, moderate and high growth development pathways. For all three
development pathways, it is possible to reject null hypotheses that innovation commitment is
the same over the four years of the longitudinal panel. The suggestion here is that, regardless
of their growth aspirations, individual businesses tend to change their commitment to
innovation over time. Together, the findings for research and development commitment and
for innovation commitment add to equivocation about the significance and/or persistence of
the linkage between manufacturing SME growth and innovation
Anticipating SME Growth Potential from Exporting and Innovation Behaviour
It remains to ascertain whether knowledge of linkages between growth, exporting and
innovation amongst manufacturing SMEs in the study sample can be reliably used to
anticipate the growth potential of manufacturing SMEs for, say, research and government
support purposes.
Because of the categorical nature of the dependent variable (SME development
pathway with three values for low growth, moderate growth and high growth), the
appropriate analytical procedure for anticipating the growth potential of the manufacturing
concerns investigated is logistic regression. The assumptions underlying logistic regression
are undemanding and its use with the irregularly distributed data available to the present
study is entirely appropriate (Aldrich & Nelson, 1984). For research and government support
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purposes, the main consideration in evaluating models of this kind is the minimisation of
Type 2 errors – that is, avoiding identification of a business as a non-growth SME when, in
fact, it is a growth SME. The possible economic costs of failing to recognise a high growth
SME in need of support require no elaboration.
In these circumstances, the most important means for assessing the goodness-of-fit of a
logistic regression model is through its classification success. Classification is usually
achieved by assigning each case to the dependent variable category for which the estimated
probability exceeds 0.5. Key statistics include the proportion of classifications that are correct
by dependent variable category. A comparison of the overall classification success with an
arbitrary benchmark of being 50 per cent correct (achievable through the toss of a fair coin) is
also of interest (Peel & Peel, 1988). Focusing on dichotomous logistic regression, Hosmer &
Lemeshow (1989, p. 147) note that:
Classification is sensitive to the relative sizes of the two component groups and will
always favour classification into the larger group, a fact that is also independent of the
fit of the model.
Ohlson (1980) also observes that logistic regression is not a technique designed to find an
optimal trade-off between Type 1 and Type 2 errors.
Preliminary model building that attempted to correctly classify manufacturing
businesses over the three SME development pathways (that is, with a trichotomous dependent
variable) using exporting and innovation measures in the BLS data as independent variables
proved to be most discouraging. In the main, classification success was markedly worse than
the toss of a fair coin. For this reason, binary logistic regression with a dichotomous
dependent variable distinguishing high growth SMEs from other concerns (low and moderate
growth SMEs) was trialled. A justification for this approach is that it is high growth SMEs
that are of greatest interest. Their identification, often referred to in the relevant literature as
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‘picking winners’, has been a major preoccupation of researchers and policy-makers worldwide (Turok, 1991).
Findings on classification success for certain binary logistic regression models are
presented in Table 6. It can be seen that logistic regression models using exporter, innovator,
and exporter and innovator status over the four years of the longitudinal panel as independent
variables, either separately or together, produce zero classification success for the 39 high
growth SMEs in the study sample. Furthermore, even when the status variables are
supplemented with variables reflecting export intensity, research and development
commitment, and innovation commitment, the classification success for high growth SMEs
remains zero.
Although they had already been employed in derivation of the export intensity, research
and development commitment, and innovation commitment variables, it was decided to also
trial as independent variables the absolute dollar values for export sales, research and
development expenditure, and innovation expenditure over the four years of the longitudinal
panel. Such variables obviously introduce an element of enterprise size or scale to the
modelling. Using these variables together with exporter, innovator, and exporter and
innovator status produces a classification success of just 15.4 per cent for high growth SMEs.
However, when all export and innovation behaviour measures that have been identified are
included as independent variables a more encouraging classification success of 74.4 per cent
is produced for high growth SMEs. Clearly, this is markedly better than a benchmark of
being 50 per cent correct. Stepwise elimination of non-statistically significant independent
variables inevitably resulted in poorer classification success. Thus, all export and innovation
behaviour measures for all four years of the BLS panel are required as independent variables
to produce maximum classification success for the high growth SMEs studied.
21
A major limitation of the predictive modelling undertaken should be acknowledged.
Classification success for a logistic regression model can be determined for the original
sample from which the model has been developed, for a sample withheld from the original
data set, or for an entirely new set of data. On the need for validation of a logistic regression
model with data other than that from which it has been developed, Hosmer & Lemeshow
(1989, p. 171) comment as follows:
The reason for considering this type of assessment of model performance is that the
fitted model always performs in an optimistic manner on the developmental data set.
In the present exploratory context, classification success has been evaluated only for the
original modelling sample. A hold-out sample was not practical since there are only 39 high
growth SMEs in the on-going longitudinal panel of 871 manufacturing SMEs. Furthermore,
no external validation has been undertaken using data from an entirely separate source
because, for cost and other reasons, such data are not available to the researcher.
CONCLUSIONS
Based on evidence presented, the first broad hypothesis for testing in this research has
substantial but not complete support. Linkages between growth, exporting and innovation do
appear to exist amongst Australian manufacturing SMEs in the BLS panel. In the main, these
linkages are statistically significant; and some of them do seem to persist over time. There is
a strong suggestion that innovation is a less significant and/or less consistent concomitant
with SME growth than exporting. An explanation for this could be that innovation is an
intrinsically cyclical activity, with periods of innovative effort being followed by some time
for commercial consolidation. Eventually, technological change, increased competitive
pressure or some such trigger may necessitate another period of innovative effort to ensure
continued success. In contrast, once initiated, export activity is much more likely to be an ongoing and regular commitment to overseas customers secured.
22
Based on evidence presented, support is less compelling for the second broad
hypothesis for testing in this research. It would appear that, using export and innovation
behaviour variables available in the BLS data, success in anticipating the growth potential of
the manufacturing SMEs studied can, at best, be described as modest. Using a cumbersome
logistic regression model with all export and innovation behaviour measures for all four years
of the longitudinal panel as independent variables, the best achievable classification success
for high growth SMEs is around 75 per cent. Of the 39 high growth SMEs in the data set, 10
are not identified as such. From the viewpoint of researchers and policy-makers, the
economic consequences of this degree of failure could, of course, be non-trivial. Thus, it
would seem to have been demonstrated that, while export and innovation behaviour are
useful pointers to growth potential, there is a need to look more widely for growth correlates
if the holy grail of being able to reliably ‘pick winners’ amongst manufacturing SMEs is ever
to be realised.
23
REFERENCES
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Bureau of Industry Economics. 1994. A Report of Small Business Innovation. Small Business
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Foundation, University of Stirling, Scotland.
McKinsey & Company. 1993. Emerging Exporters: Australia’s High Value-Added
Manufacturing Exporters. Melbourne, Victoria: Australian Manufacturing Council.
24
McKinsey & Company. 1994. The Wealth of Ideas: How Linkages Help Sustain Innovation
and Growth. Melbourne, Victoria: Australian Manufacturing Council.
McMahon, R.G.P. Forthcoming. Deriving an empirical development taxonomy for
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Financial Management: Theory and Practice. Sydney, New South Wales: Harcourt Brace.
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Peel, M.J. & D.A. Peel. 1988. A multilogit approach to predicting corporate failure – some
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Turok, I. 1991. Which small firms grow?. In L.G. Davies & A.A. Gibb, editors, Recent
Research in Entrepreneurship. England: Avebury.
Vozikis, G.S. & W. Mescon. 1988. Stages of development and stages of the exporting
process in a small business context. In R.J. Rudd, W.T. Greenwood & F.W. Becker,
editors, Small Business in a Regulated Economy: Issues and Policy Indications. New
York, New York: Quorom Books.
25
Table 1: FREQUENCY DISTRIBUTIONS FOR GROWTH,
EXPORTING AND INNOVATING SMEs
Innovatorsb
Exporters &
Innovators
Exportersa
Innovatorsb
Exporters &
Innovators
Exportersa
Innovatorsb
Exporters &
Innovators
High growth
SMEs (n=39)
Exportersa
Moderate growth
SMEs (n=203)
232
242
104
215
193
82
199
131
71
207
112
63
36.9%
38.5%
16.5%
34.2%
30.7%
13.0%
31.6%
20.8%
11.3%
32.9%
17.8%
10.0%
112
109
65
114
82
56
117
51
37
122
61
45
55.2%
53.7%
32.0%
56.2%
40.4%
27.6%
57.6%
25.1%
18.2%
60.1%
30.0%
22.2%
22
26
17
27
16
13
24
12
10
24
15
12
56.4%
66.7%
43.6%
69.2%
41.0%
33.3%
61.5%
30.8%
25.6%
61.5%
38.5%
30.8%
a Includes both innovating and non-innovating SMEs.
b
1997-98
Exporters &
Innovators
Low growth
SMEs (n=629)
1996-97
Innovatorsb
Growth Pathway
1995-96
Exportersa
1994-95
Includes both exporting and non-exporting SMEs.
26
Table 2: EXPORT INTENSITY AND R&D/INNOVATION COMMITMENT
STATISTICS FOR SME GROWTH PATHWAYSa
a
R&D
Commitmentc
Innovation
Commitmentd
Export
Intensityb
R&D
Commitmentc
Innovation
Commitmentd
Export
Intensityb
R&D
Commitmentc
Innovation
Commitmentd
High growth
SMEs (n=39)
Export
Intensityb
Moderate growth
SMEs (n=203)
1997-98
Innovation
Commitmentd
Low growth
SMEs (n=629)
1996-97
R&D
Commitmentc
Growth Pathway
1995-96
Export
Intensityb
1994-95
5.0
1.5
3.1
5.3
1.2
n.a.
5.2
1.0
1.4
5.0
1.0
1.1
14.5
6.5
11.4
14.6
6.5
n.a.
14.5
6.4
7.3
14.0
5.3
4.8
2.9
4.3
3.7
2.8
5.4
n.a.
2.8
6.4
5.2
2.8
5.3
4.4
7.4
0.8
2.3
8.1
0.8
n.a.
8.7
0.5
0.7
8.5
0.6
1.4
17.3
2.4
5.4
16.9
2.7
n.a.
18.1
1.7
1.9
17.6
2.7
6.0
2.3
3.0
2.3
2.1
3.4
n.a.
2.1
3.4
2.7
2.1
4.5
4.3
8.5
0.8
1.6
10.6
0.6
n.a.
8.9
0.5
0.8
9.3
0.6
0.8
17.6
1.5
2.3
19.8
1.5
n.a.
18.5
1.6
1.8
20.8
1.7
2.0
2.1
1.9
1.4
1.9
2.5
n.a.
2.1
3.2
2.3
2.2
2.8
2.5
Statistics are mean, standard deviation and coefficient of variation.
Export intensity = (Annual export sales/Annual total sales) x 100%.
c
R&D commitment = (Annual R&D expenditure/Annual total sales) x 100%.
d
Innovation commitment = (Annual innovation expenditure/Annual total sales) x 100%.
b
27
Table 3: 2 TESTS FOR GROWTH, EXPORTING AND INNOVATING SMEs
Test Values
Test Variables
Test Details
Exporter status
vs
Innovator status
2 statistic
df
Significance
Growth pathway
vs
Exporter status
2 statistic
df
Significance
Growth pathway
vs
Innovator status
2 statistic
df
Significance
Growth pathway
vs
Exporter &
Innovator status
2 statistic
df
Significance
1994-95
1995-96
1996-97
1997-98
14.604
21.950
49.794
54.008
1
1
1
1
0.000
0.000
0.000
0.000
24.539
44.256
52.275
54.548
2
2
2
2
0.000
0.000
0.000
0.000
23.577
7.569
3.339
20.463
2
2
2
2
0.000
0.023
0.188
0.000
33.932
29.961
11.407
29.000
2
2
2
2
0.000
0.000
0.003
0.000
28
Table 4: KRUSKAL-WALLIS TESTS FOR EXPORT INTENSITY
AND R&D/INNOVATION COMMITMENT
Test Values
1994-95
1995-96
1996-97
1997-98
29.415
60.476
50.970
61.166
1
1
1
1
0.000
0.000
0.000
0.000
12.573
n.a.
53.713
50.921
1
n.a.
1
1
0.000
n.a.
0.000
0.000
17.220
23.171
51.325
51.427
1
1
1
1
0.000
0.000
0.000
0.000
23.739
40.324
48.921
49.736
2
2
2
2
Significance
0.000
0.000
0.000
0.000
Kruskal-Wallis statistic
7.619
21.783
1.376
11.357
2
2
2
2
Significance
0.022
0.000
0.503
0.003
Kruskal-Wallis statistic
7.331
n.a.
2.588
16.477
2
n.a.
2
2
0.026
n.a.
0.274
0.000
Test Variables
Test Details
Exporter status
vs
R&D commitment
Kruskal-Wallis statistic
df
Significance
Exporter status
vs
Innovation
commitment
Kruskal-Wallis statistic
df
Significance
Innovator status
vs
Export intensity
Kruskal-Wallis statistic
df
Significance
Growth pathway
vs
Export intensity
Growth pathway
vs
R&D commitment
Growth pathway
vs
Innovation
commitment
Kruskal-Wallis statistic
df
df
df
Significance
29
Table 5: FRIEDMAN TESTS FOR GROWTH, EXPORTING
AND INNOVATING SMEs
Test Values
Export/Innovation
Measure
Test Details
Exporter status
Low growth SMEs (n=629)
Innovator status
Exporter &
Innovator status
Export intensity
R&D commitment
df
Significance
17.947
3
0.000
Moderate growth SMEs (n=203)
3.721
3
0.293
High growth SMEs (n=39)
4.636
3
0.200
122.745
3
0.000
Moderate growth SMEs (n=203)
55.238
3
0.000
High growth SMEs (n=39)
15.276
3
0.002
Low growth SMEs (n=629)
24.675
3
0.000
Moderate growth SMEs (n=203)
17.248
3
0.001
High growth SMEs (n=39)
4.216
3
0.239
Low growth SMEs (n=629)
1.256
3
0.740
Moderate growth SMEs (n=203)
6.693
3
0.082
High growth SMEs (n=39)
1.879
3
0.598
Low growth SMEs (n=629)
84.643
3
0.000
Moderate growth SMEs (n=203)
37.241
3
0.000
4.176
3
0.243
115.282
2
0.000
51.029
2
0.000
9.556
2
0.008
Low growth SMEs (n=629)
High growth SMEs (n=39)
Innovation
commitment
Statistic
Low growth SMEs (n=629)
Moderate growth SMEs (n=203)
High growth SMEs (n=39)
30
Table 6: CLASSIFICATION SUCCESS FOR LOGISTIC
REGRESSION MODELS (n=871)
Predicted Classification
Independent Variable(s)
(from 1994-95 to 1997-98)
Exporter status
Observed
Classification
Not high growth
High growth
Innovator status
Not high growth
High growth
Exporter & innovator status
Not high growth
High growth
Exporter status
+ Innovator status
Exporter status
+ Innovator status
+ Exporter & innovator status
Exporter/innovator status variables (as above)
+ Export intensity and R&D/innovation commitment
Exporter/innovator status variables
+ Annual export sales, R&D expenditure and
innovation expenditure
Exporter/innovator status variables
+ Export intensity and R&D/innovation commitment
+ Annual export sales, R&D expenditure and
innovation expenditure
Not high growth
High growth
Not high growth
High growth
Not high growth
High growth
Not high growth
High growth
Not high growth
High growth
Not High
Growth
High
Growth
Per Cent
Correct
832
0
100.0
39
0
0.0
Overall per cent correct
95.5
832
0
100.0
39
0
0.0
Overall per cent correct
95.5
832
0
100.0
39
0
0.0
Overall per cent correct
95.5
832
0
100.0
39
0
0.0
Overall per cent correct
95.5
832
0
100.0
39
0
0.0
Overall per cent correct
95.5
832
0
100.0
39
0
0.0
Overall per cent correct
95.5
829
3
99.6
33
6
15.4
Overall per cent correct
95.9
830
2
99.8
10
29
74.4
Overall per cent correct
98.6