dissertation in pdf-format - Aalto-yliopisto

Characteristics of successful gazelles 25
GB growth of the branch of industry
HR the number of staff employed by the firm
PF profitability factor
RI the number of intellectual property rights (radical innovations).
The signs of the first derivatives of the explanatory factors are shown under the
equations. It was expected that the number and annual growth of staff (Veronique et al.,
2000), the growth of the branch of industry (Audretsch, 1995; Markman and Gartner,
2002), the number of IPRs (Heimonen, 2012), the success of the firm (Davidsson et al.,
2009; Steffens et al., 2009) and being located in an urban area (theories of
resource-munificence and regional competitiveness) would have a positive effect on
growth of the firm. The expected impact of predictor variables would otherwise be the
same, but with success index treated as a dependent variable and growth of sales turnover
as an independent variable. The age of a firm was expected to have a positive impact on
growth (Cooper, 1993; Heimonen and Virtanen, 2007; Littunen and Virtanen, 2006) and
a negative impact on success (Birley and Westhead, 1990).
Factor analysis was completed in order to identify the main dimensions of the
financial data. Four factors profitability, liquidity, solvency and business volume with
eigenvalues of more than one were found to explain about 70% of the variation in the
financial data.
Stepwise regression was applied separately in the growth and success models
(Tables 1 and 2). The best model for growth included the variables logarithmic
transformation of the number of staff, company age and IPRs. Moreover, the
profitability factor and branch of industry (trade) and region were found to be
statistically significant explanatory variables. In the success model, age and IPRs were
not statistically significant but the number of auxiliary business names was included in
the model. Two dichotomic variables, manufacturing and transportation +
telecommunication, were statistically significant but they were different from the growth
model dummy (trade). The results of the growth model are consistent with, for example,
Delmar (1997) so that the younger the firm the higher the growth, but contradict Littunen
and Virtanen (2006) and Heimonen and Virtanen (2007) who, like Cooper (1993),
concluded that the age of a firm has a positive impact on its growth. However, it should
be noted that we have used age of the firm, not age of the entrepreneur, as the
explanatory variable.
We would expect that the number of innovation inputs (IPRs) would have a
positive impact on the growth of a firm. It seems that the higher the total number of
innovation inputs the higher the growth of the business. Contrary to our previous paper
(Heimonen and Virtanen, 2007), region seems to have some effect on growth rate
but not on success. Growth seemed to be slightly higher in the urban area. One interesting
detail is that the growth in the number of staff seems to have a negative effect on success
but a positive impact on growth. Thus those businesses employing more people
during their development will have a lower level of success. We could argue that, in the
short run, an increase in employment would decrease the profitability of growing
businesses.