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404 J. Siikonen et al.
4 Results
4.1 Distinguishing characteristics of the high-growth sectors compared to other
industrial branches
In order to address the main research question, we first discuss the results regarding the
previously presented sub-questions (i.e., acquired information on the branches of industry
that grew rapidly in Eastern Finland in the study period, and their distinguishing
characteristics relative to other branches of industries with growing firms). We found that
the services sector was the only fast-growth branch of industry during the period 2002 to
2005 in Eastern Finland. In addition, we identified several factors that may differentiate
the service sector, including KIBS growth firms, from the growth firms in other sectors,
such as trade, manufacturing, construction, transportation and telecommunication.
The results presented in Table 2 show the overall distribution of growth firms
according to their branch of industry among the firms considered. Not all firms were
included in the Logistic regression analyses (LR-analyses) because there were fewer
services firms (216) than firms representing other branches (350). This imbalance, in the
absence of appropriate adjustment, would have led to bias regarding the role and
influence of the larger group in LR-analysis. Therefore, we included only part of the data
regarding other industry branches in the LR-analysis, and used the remainder of the other
industry data for cross-validation of the results, i.e., to assess the validity and reliability
of the results. Hence, 433 firms were included in the analysis, 133 firms defined as other
branch of industry firms were used in the cross-validation (and one firm for which data
for some variables were missing was excluded). Both an Omnibus test of model
coefficients and a Hosmer and Lemeshow test of correct classification (p > 0.05)
indicated that the model can reliably differentiate services growth firms from growth
firms representing other branches of industry (e.g., trade, manufacturing, construction
and transportation/telecommunication).
We also used binary logistic analysis in an attempt to identify common characteristics
of the fast-growth KIBS firms in a specific rural area (Eastern Finland). For this purpose
we first studied variables and factors capable of differentiating services firms from firms
representing other branches of industry (using the binary classification system described
above). The independent variables and factors that were found to be statistically
significant differentiators in the model were:
1 the number of auxiliary business names
2 age of the firm
3 growth of the branch of industry
4 success class
5 growth class
6 log-transformed public R&D funding received.
We logarithmically transformed public R&D funding values to reduce the wide ranges of
this variable. The location of the firm did not appear to be a statistically significant factor
for differentiating between these branches of industry. In other words, this model seems
to fit firms in both a rural area (Eastern Finland) and an urban area (the capital area of
Finland).